The Data Science Course Complete Data Science Bootcamp
Language: English | Size:9.08 GB
Genre:eLearning
Files Included :
001 A Practical Example What U Will Learn in This Course.mp4 (43.94 MB)
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002 What Does the Course Covers.mp4 (51.36 MB)
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001 Data Science and Business Buzzwords Why are there so Many.mp4 (57.35 MB)
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002 What is the difference between Analysis and Analytics.mp4 (11.16 MB)
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003 Business Analytics, Data Analytics, and Data Science An Introduction.mp4 (52.62 MB)
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004 Continuing with BI, ML, and AI.mp4 (36.95 MB)
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005 A Breakdown of our Data Science Infographic.mp4 (45.3 MB)
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001 The Reason Behind These Disciplines.mp4 (46.7 MB)
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001 Techniques for Working with Traditional Data.mp4 (107.39 MB)
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002 Real Life Examples of Traditional Data.mp4 (18.37 MB)
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003 Techniques for Working with Big Data.mp4 (62.11 MB)
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004 Real Life Examples of Big Data.mp4 (13.07 MB)
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005 Business Intelligence (BI) Techniques.mp4 (52.88 MB)
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006 Real Life Examples of Business Intelligence (BI).mp4 (24.68 MB)
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007 Techniques for Working with Traditional Methods.mp4 (76.1 MB)
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008 Real Life Examples of Traditional Methods.mp4 (27.41 MB)
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009 Machine Learning (ML) Techniques.mp4 (49.41 MB)
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010 Types of Machine Learning.mp4 (80.57 MB)
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011 Real Life Examples of Machine Learning (ML).mp4 (27.7 MB)
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001 Finding the Job - What to Expect and What to Look for.mp4 (13.81 MB)
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001 Debunking Common Misconceptions.mp4 (58.81 MB)
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001 The Basic Probability Formula.mp4 (29.39 MB)
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002 Computing Expected Values.mp4 (45.67 MB)
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003 Frequency.mp4 (37.36 MB)
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004 Events and Their Complements.mp4 (25.83 MB)
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001 Fundamentals of Combinatorics.mp4 (5.95 MB)
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002 Permutations and How to Use Them.mp4 (17.52 MB)
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003 Simple Operations with Factorials.mp4 (16.68 MB)
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004 Solving Variations with Repetition.mp4 (13.95 MB)
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005 Solving Variations without Repetition.mp4 (18.25 MB)
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006 Solving Combinations.mp4 (23.67 MB)
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007 Symmetry of Combinations.mp4 (13.75 MB)
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008 Solving Combinations with Separate Sample Spaces.mp4 (10.65 MB)
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009 Combinatorics in Real-Life The Lottery.mp4 (16.39 MB)
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010 A Recap of Combinatorics.mp4 (15.02 MB)
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011 A Practical Example of Combinatorics.mp4 (42.8 MB)
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001 Sets and Events.mp4 (17.65 MB)
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002 Ways Sets Can Interact.mp4 (19.3 MB)
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003 Intersection of Sets.mp4 (11.01 MB)
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004 Union of Sets.mp4 (24.2 MB)
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005 Mutually Exclusive Sets.mp4 (10.59 MB)
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006 Dependence and Independence of Sets.mp4 (14.92 MB)
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007 The Conditional Probability Formula.mp4 (16.59 MB)
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008 The Law of Total Probability.mp4 (11.59 MB)
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009 The Additive Rule.mp4 (11.11 MB)
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010 The Multiplication Law.mp4 (20.19 MB)
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011 Bayes' Law.mp4 (21.34 MB)
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012 A Practical Example of Bayesian Inference.mp4 (139.14 MB)
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001 Fundamentals of Probability Distributions.mp4 (19.43 MB)
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002 Types of Probability Distributions.mp4 (35.58 MB)
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003 Characteristics of Discrete Distributions.mp4 (9.42 MB)
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004 Discrete Distributions The Uniform Distribution.mp4 (10.31 MB)
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005 Discrete Distributions The Bernoulli Distribution.mp4 (15.12 MB)
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006 Discrete Distributions The Binomial Distribution.mp4 (30.61 MB)
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007 Discrete Distributions The Poisson Distribution.mp4 (23.93 MB)
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008 Characteristics of Continuous Distributions.mp4 (36.13 MB)
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009 Continuous Distributions The Normal Distribution.mp4 (20.01 MB)
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010 Continuous Distributions The Standard Normal Distribution.mp4 (38.36 MB)
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011 Continuous Distributions The Students' T Distribution.mp4 (9.24 MB)
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012 Continuous Distributions The Chi-Squared Distribution.mp4 (20.97 MB)
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013 Continuous Distributions The Exponential Distribution.mp4 (16 MB)
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014 Continuous Distributions The Logistic Distribution.mp4 (16.17 MB)
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015 A Practical Example of Probability Distributions.mp4 (138.12 MB)
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001 Probability in Finance.mp4 (40.34 MB)
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002 Probability in Statistics.mp4 (31.6 MB)
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003 Probability in Data Science.mp4 (56.89 MB)
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001 Population and Sample.mp4 (35.1 MB)
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001 Types of Data.mp4 (43.17 MB)
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002 Levels of Measurement.mp4 (32.18 MB)
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003 Categorical Variables - Visualization Techniques.mp4 (36.64 MB)
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005 Numerical Variables - Frequency Distribution Table.mp4 (17.69 MB)
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007 The Histogram.mp4 (9.57 MB)
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009 Cross Tables and Scatter Plots.mp4 (19.71 MB)
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011 Mean, median and mode.mp4 (24.49 MB)
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013 Skewness.mp4 (13.31 MB)
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015 Variance.mp4 (23.54 MB)
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017 Standard Deviation and Coefficient of Variation.mp4 (20.14 MB)
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019 Covariance.mp4 (18.38 MB)
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021 Correlation Coefficient.mp4 (19.34 MB)
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001 Practical Example Descriptive Statistics.mp4 (150.18 MB)
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001 Introduction.mp4 (3.06 MB)
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002 What is a Distribution.mp4 (17.2 MB)
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003 The Normal Distribution.mp4 (27.49 MB)
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004 The Standard Normal Distribution.mp4 (8.61 MB)
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006 Central Limit Theorem.mp4 (23.22 MB)
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007 Standard error.mp4 (13.52 MB)
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008 Estimators and Estimates.mp4 (27.7 MB)
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001 What are Confidence Intervals.mp4 (28.62 MB)
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002 Confidence Intervals; Population Variance Known; Z-score.mp4 (52.16 MB)
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004 Confidence Interval Clarifications.mp4 (18.94 MB)
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005 Student's T Distribution.mp4 (13.68 MB)
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006 Confidence Intervals; Population Variance Unknown; T-score.mp4 (13.69 MB)
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008 Margin of Error.mp4 (23.1 MB)
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009 Confidence intervals Two means Dependent samples.mp4 (44.97 MB)
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011 Confidence intervals Two means Independent Samples (Part 1).mp4 (11.99 MB)
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013 Confidence intervals Two means Independent Samples (Part 2).mp4 (14.62 MB)
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015 Confidence intervals Two means Independent Samples (Part 3).mp4 (6.89 MB)
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001 Practical Example Inferential Statistics.mp4 (68.98 MB)
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001 Null vs Alternative Hypothesis.mp4 (83.58 MB)
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003 Rejection Region and Significance Level.mp4 (38.69 MB)
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004 Type I Error and Type II Error.mp4 (18.61 MB)
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005 Test for the Mean Population Variance Known.mp4 (36.95 MB)
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007 p-value.mp4 (33.78 MB)
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008 Test for the Mean Population Variance Unknown.mp4 (19.71 MB)
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010 Test for the Mean Dependent Samples.mp4 (32.79 MB)
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012 Test for the mean Independent Samples (Part 1).mp4 (15.41 MB)
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014 Test for the mean Independent Samples (Part 2).mp4 (24.45 MB)
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001 Practical Example Hypothesis Testing.mp4 (45.82 MB)
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001 Introduction to Programming.mp4 (14.76 MB)
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002 Why Python.mp4 (12.04 MB)
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003 Why Jupyter.mp4 (8.13 MB)
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004 Installing Python and Jupyter.mp4 (32.82 MB)
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005 Understanding Jupyter's Interface - the Notebook Dashboard.mp4 (6.07 MB)
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006 Prerequisites for Coding in the Jupyter Notebooks.mp4 (18.96 MB)
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001 Variables.mp4 (8.95 MB)
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002 Numbers and Boolean Values in Python.mp4 (13.7 MB)
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003 Python Strings.mp4 (15.67 MB)
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001 Using Arithmetic Operators in Python.mp4 (8.63 MB)
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002 The Double Equality Sign.mp4 (2.72 MB)
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003 How to Reassign Values.mp4 (1.86 MB)
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004 Add Comments.mp4 (2.41 MB)
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005 Understanding Line Continuation.mp4 (1.2 MB)
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006 Indexing Elements.mp4 (2.36 MB)
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007 Structuring with Indentation.mp4 (2.79 MB)
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001 Comparison Operators.mp4 (4.82 MB)
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002 Logical and Identity Operators.mp4 (19 MB)
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001 The IF Statement.mp4 (6.07 MB)
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002 The ELSE Statement.mp4 (6.04 MB)
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003 The ELIF Statement.mp4 (14.23 MB)
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004 A Note on Boolean Values.mp4 (4.24 MB)
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001 Defining a Function in Python.mp4 (3.23 MB)
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002 How to Create a Function with a Parameter.mp4 (8.33 MB)
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003 Defining a Function in Python - Part II.mp4 (6.45 MB)
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004 How to Use a Function within a Function.mp4 (3.23 MB)
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005 Conditional Statements and Functions.mp4 (5.98 MB)
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006 Functions Containing a Few Arguments.mp4 (2.83 MB)
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007 Built-in Functions in Python.mp4 (10.19 MB)
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001 Lists.mp4 (23.03 MB)
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002 Using Methods.mp4 (30.37 MB)
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003 List Slicing.mp4 (19.18 MB)
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004 Tuples.mp4 (18.19 MB)
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005 Dictionaries.mp4 (32.44 MB)
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001 For Loops.mp4 (23.6 MB)
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002 While Loops and Incrementing.mp4 (20.18 MB)
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003 Lists with the range() Function.mp4 (11.94 MB)
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004 Conditional Statements and Loops.mp4 (21.94 MB)
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005 Conditional Statements, Functions, and Loops.mp4 (4.27 MB)
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006 How to Iterate over Dictionaries.mp4 (16.44 MB)
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001 Object Oriented Programming.mp4 (8.65 MB)
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002 Modules and Packages.mp4 (2.08 MB)
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003 What is the Standard Library.mp4 (5.05 MB)
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004 Importing Modules in Python.mp4 (8.55 MB)
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001 Introduction to Regression Analysis.mp4 (3.59 MB)
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001 The Linear Regression Model.mp4 (13.48 MB)
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002 Correlation vs Regression.mp4 (3.84 MB)
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004 Python Packages Installation.mp4 (23.67 MB)
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005 First Regression in Python.mp4 (29.62 MB)
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007 Using Seaborn for Graphs.mp4 (7.37 MB)
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008 How to Interpret the Regression Table.mp4 (28.73 MB)
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009 Decomposition of Variability.mp4 (8.79 MB)
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010 What is the OLS.mp4 (22.48 MB)
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011 R-Squared.mp4 (11.2 MB)
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001 Multiple Linear Regression.mp4 (5.68 MB)
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002 Adjusted R-Squared.mp4 (34.19 MB)
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004 Test for Significance of the Model (F-Test).mp4 (7.17 MB)
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005 OLS Assumptions.mp4 (5.26 MB)
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006 A1 Linearity.mp4 (3.57 MB)
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007 A2 No Endogeneity.mp4 (9.24 MB)
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008 A3 Normality and Homoscedasticity.mp4 (27.38 MB)
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009 A4 No Autocorrelation.mp4 (7.89 MB)
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010 A5 No Multicollinearity.mp4 (7.6 MB)
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002 How are we Going to Approach this Section.mp4 (5.29 MB)
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003 Simple Linear Regression with sklearn.mp4 (31.62 MB)
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004 Simple Linear Regression with sklearn - A StatsModels-like Summary Table.mp4 (28.89 MB)
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007 Multiple Linear Regression with sklearn.mp4 (11.01 MB)
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008 Calculating the Adjusted R-Squared in sklearn.mp4 (21.75 MB)
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010 Feature Selection (F-regression).mp4 (20.47 MB)
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012 Creating a Summary Table with P-values.mp4 (6.45 MB)
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014 Feature Scaling (Standardization).mp4 (20.36 MB)
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015 Feature Selection through Standardization of Weights.mp4 (24.46 MB)
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016 Predicting with the Standardized Coefficients.mp4 (20.42 MB)
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018 Underfitting and Overfitting.mp4 (5.83 MB)
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019 Train - Test Split Explained.mp4 (35.57 MB)
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001 Practical Example Linear Regression (Part 1).mp4 (84.69 MB)
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002 Practical Example Linear Regression (Part 2).mp4 (31.88 MB)
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004 Practical Example Linear Regression (Part 3).mp4 (16.65 MB)
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006 Practical Example Linear Regression (Part 4).mp4 (39.4 MB)
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008 Practical Example Linear Regression (Part 5).mp4 (50.4 MB)
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001 Introduction to Logistic Regression.mp4 (5.87 MB)
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002 A Simple Example in Python.mp4 (21.89 MB)
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003 Logistic vs Logit Function.mp4 (23.76 MB)
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004 Building a Logistic Regression.mp4 (8.59 MB)
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006 An Invaluable Coding Tip.mp4 (18.76 MB)
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007 Understanding Logistic Regression Tables.mp4 (14.58 MB)
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009 What do the Odds Actually Mean.mp4 (11.39 MB)
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010 Binary Predictors in a Logistic Regression.mp4 (24.83 MB)
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012 Calculating the Accuracy of the Model.mp4 (20.27 MB)
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014 Underfitting and Overfitting.mp4 (7.49 MB)
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015 Testing the Model.mp4 (21.59 MB)
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001 Introduction to Cluster Analysis.mp4 (14.46 MB)
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002 Some Examples of Clusters.mp4 (35.87 MB)
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003 Difference between Classification and Clustering.mp4 (9.67 MB)
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004 Math Prerequisites.mp4 (5.27 MB)
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001 K-Means Clustering.mp4 (10.82 MB)
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002 A Simple Example of Clustering.mp4 (34.21 MB)
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004 Clustering Categorical Data.mp4 (10.35 MB)
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006 How to Choose the Number of Clusters.mp4 (26.87 MB)
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008 Pros and Cons of K-Means Clustering.mp4 (11.12 MB)
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009 To Standardize or not to Standardize.mp4 (10.92 MB)
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010 Relationship between Clustering and Regression.mp4 (3.51 MB)
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011 Market Segmentation with Cluster Analysis (Part 1).mp4 (28.09 MB)
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012 Market Segmentation with Cluster Analysis (Part 2).mp4 (34.09 MB)
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013 How is Clustering Useful.mp4 (37.48 MB)
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001 Types of Clustering.mp4 (9.01 MB)
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002 Dendrogram.mp4 (18.3 MB)
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003 Heatmaps.mp4 (25.71 MB)
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001 What is a Matrix.mp4 (11.94 MB)
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002 Scalars and Vectors.mp4 (8.53 MB)
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003 Linear Algebra and Geometry.mp4 (13.73 MB)
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004 Arrays in Python - A Convenient Way To Represent Matrices.mp4 (18.98 MB)
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005 What is a Tensor.mp4 (15.53 MB)
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006 Addition and Subtraction of Matrices.mp4 (22.1 MB)
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007 Errors when Adding Matrices.mp4 (5.78 MB)
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008 Transpose of a Matrix.mp4 (20.49 MB)
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009 Dot Product.mp4 (12.84 MB)
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010 Dot Product of Matrices.mp4 (34.32 MB)
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011 Why is Linear Algebra Useful.mp4 (88.42 MB)
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001 What to Expect from this Part.mp4 (11.73 MB)
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001 Introduction to Neural Networks.mp4 (10.49 MB)
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002 Training the Model.mp4 (7.71 MB)
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003 Types of Machine Learning.mp4 (13.05 MB)
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004 The Linear Model (Linear Algebraic Version).mp4 (7.98 MB)
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005 The Linear Model with Multiple Inputs.mp4 (7.91 MB)
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006 The Linear model with Multiple Inputs and Multiple Outputs.mp4 (16.66 MB)
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007 Graphical Representation of Simple Neural Networks.mp4 (7.78 MB)
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008 What is the Objective Function.mp4 (6.18 MB)
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009 Common Objective Functions L2-norm Loss.mp4 (5.47 MB)
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010 Common Objective Functions Cross-Entropy Loss.mp4 (9.84 MB)
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011 Optimization Algorithm 1-Parameter Gradient Descent.mp4 (23.59 MB)
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012 Optimization Algorithm n-Parameter Gradient Descent.mp4 (16.83 MB)
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001 Basic NN Example (Part 1).mp4 (9.34 MB)
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002 Basic NN Example (Part 2).mp4 (15.23 MB)
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003 Basic NN Example (Part 3).mp4 (15.65 MB)
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004 Basic NN Example (Part 4).mp4 (39.99 MB)
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001 How to Install TensorFlow 2 0.mp4 (27.32 MB)
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002 TensorFlow Outline and Comparison with Other Libraries.mp4 (15.28 MB)
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003 TensorFlow 1 vs TensorFlow 2.mp4 (15.32 MB)
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004 A Note on TensorFlow 2 Syntax.mp4 (4.63 MB)
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005 Types of File Formats Supporting TensorFlow.mp4 (8.86 MB)
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006 Outlining the Model with TensorFlow 2.mp4 (26.94 MB)
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007 Interpreting the Result and Extracting the Weights and Bias.mp4 (25.96 MB)
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008 Customizing a TensorFlow 2 Model.mp4 (16.71 MB)
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001 What is a Layer.mp4 (5.17 MB)
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002 What is a Deep Net.mp4 (9.12 MB)
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003 Digging into a Deep Net.mp4 (23.7 MB)
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004 Non-Linearities and their Purpose.mp4 (22.57 MB)
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005 Activation Functions.mp4 (8.85 MB)
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006 Activation Functions Softmax Activation.mp4 (8.74 MB)
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007 Backpropagation.mp4 (20.35 MB)
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008 Backpropagation Picture.mp4 (8.06 MB)
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001 What is Overfitting.mp4 (10.81 MB)
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002 Underfitting and Overfitting for Classification.mp4 (14 MB)
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003 What is Validation.mp4 (8.38 MB)
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004 Training, Validation, and Test Datasets.mp4 (9.4 MB)
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005 N-Fold Cross Validation.mp4 (6.24 MB)
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006 Early Stopping or When to Stop Training.mp4 (10.29 MB)
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001 What is Initialization.mp4 (12.85 MB)
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002 Types of Simple Initializations.mp4 (5.73 MB)
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003 State-of-the-Art Method - (Xavier) Glorot Initialization.mp4 (5.46 MB)
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001 Stochastic Gradient Descent.mp4 (9.67 MB)
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002 Problems with Gradient Descent.mp4 (3.65 MB)
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003 Momentum.mp4 (5.18 MB)
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005 Learning Rate Schedules Visualized.mp4 (8 MB)
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007 Adam (Adaptive Moment Estimation).mp4 (7.14 MB)
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001 Preprocessing Introduction.mp4 (9.23 MB)
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002 Types of Basic Preprocessing.mp4 (3.24 MB)
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003 Standardization.mp4 (12.07 MB)
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004 Preprocessing Categorical Data.mp4 (5.44 MB)
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005 Binary and One-Hot Encoding.mp4 (23.94 MB)
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001 MNIST The Dataset.mp4 (4.53 MB)
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002 MNIST How to Tackle the MNIST.mp4 (7.95 MB)
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003 MNIST Importing the Relevant Packages and Loading the Data.mp4 (12.24 MB)
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004 MNIST Preprocess the Data - Create a Validation Set and Scale It.mp4 (22.9 MB)
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006 MNIST Preprocess the Data - Shuffle and Batch.mp4 (32.69 MB)
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008 MNIST Outline the Model.mp4 (22.08 MB)
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009 MNIST Select the Loss and the Optimizer.mp4 (10.63 MB)
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010 MNIST Learning.mp4 (30.99 MB)
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012 MNIST Testing the Model.mp4 (22.61 MB)
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001 Business Case Exploring the Dataset and Identifying Predictors.mp4 (51.28 MB)
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002 Business Case Outlining the Solution.mp4 (3.05 MB)
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003 Business Case Balancing the Dataset.mp4 (27.31 MB)
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004 Business Case Preprocessing the Data.mp4 (73.86 MB)
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006 Business Case Load the Preprocessed Data.mp4 (13.83 MB)
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008 Business Case Learning and Interpreting the Result.mp4 (27.77 MB)
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009 Business Case Setting an Early Stopping Mechanism.mp4 (43.75 MB)
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011 Business Case Testing the Model.mp4 (8.18 MB)
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001 Summary on What You've Learned.mp4 (9.86 MB)
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002 What's Further out there in terms of Machine Learning.mp4 (4.79 MB)
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004 An overview of CNNs.mp4 (13.38 MB)
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005 An Overview of RNNs.mp4 (6.97 MB)
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006 An Overview of non-NN Approaches.mp4 (16.08 MB)
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002 How to Install TensorFlow 1.mp4 (5 MB)
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004 TensorFlow Intro.mp4 (16.88 MB)
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005 Actual Introduction to TensorFlow.mp4 (9.15 MB)
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006 Types of File Formats, supporting Tensors.mp4 (8.89 MB)
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007 Basic NN Example with TF Inputs, Outputs, Targets, Weights, Biases.mp4 (17.7 MB)
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008 Basic NN Example with TF Loss Function and Gradient Descent.mp4 (15.7 MB)
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009 Basic NN Example with TF Model Output.mp4 (19.14 MB)
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001 MNIST What is the MNIST Dataset.mp4 (4.8 MB)
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002 MNIST How to Tackle the MNIST.mp4 (6.49 MB)
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003 MNIST Relevant Packages.mp4 (11.26 MB)
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004 MNIST Model Outline.mp4 (34.65 MB)
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005 MNIST Loss and Optimization Algorithm.mp4 (15.77 MB)
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006 Calculating the Accuracy of the Model.mp4 (24.45 MB)
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007 MNIST Batching and Early Stopping.mp4 (9.48 MB)
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008 MNIST Learning.mp4 (31.83 MB)
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009 MNIST Results and Testing.mp4 (45.47 MB)
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001 Business Case Getting Acquainted with the Dataset.mp4 (60.25 MB)
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002 Business Case Outlining the Solution.mp4 (4.16 MB)
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003 The Importance of Working with a Balanced Dataset.mp4 (27.25 MB)
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004 Business Case Preprocessing.mp4 (63.7 MB)
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006 Creating a Data Provider.mp4 (56.31 MB)
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007 Business Case Model Outline.mp4 (42.53 MB)
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008 Business Case Optimization.mp4 (26.93 MB)
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009 Business Case Interpretation.mp4 (18.6 MB)
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010 Business Case Testing the Model.mp4 (4.34 MB)
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011 Business Case A Comment on the Homework.mp4 (20.58 MB)
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001 What are Data, Servers, Clients, Requests, and Responses.mp4 (19.51 MB)
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002 What are Data Connectivity, APIs, and Endpoints.mp4 (60.23 MB)
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003 Taking a Closer Look at APIs.mp4 (67.06 MB)
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004 Communication between Software Products through Text Files.mp4 (21.87 MB)
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005 Software Integration - Explained.mp4 (42.94 MB)
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001 Game Plan for this Python, SQL, and Tableau Business Exercise.mp4 (19.67 MB)
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002 The Business Task.mp4 (8.35 MB)
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003 Introducing the Data Set.mp4 (24.24 MB)
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002 Importing the Absenteeism Data in Python.mp4 (19.53 MB)
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003 Checking the Content of the Data Set.mp4 (54.05 MB)
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004 Introduction to Terms with Multiple Meanings.mp4 (18 MB)
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006 Using a Statistical Approach towards the Solution to the Exercise.mp4 (13.75 MB)
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007 Dropping a Column from a DataFrame in Python.mp4 (41.25 MB)
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010 Analyzing the Reasons for Absence.mp4 (27.61 MB)
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011 Obtaining Dummies from a Single Feature.mp4 (69.76 MB)
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015 More on Dummy Variables A Statistical Perspective.mp4 (5.82 MB)
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016 Classifying the Various Reasons for Absence.mp4 (59.2 MB)
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017 Using concat() in Python.mp4 (27.33 MB)
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020 Reordering Columns in a Pandas DataFrame in Python.mp4 (9.99 MB)
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023 Creating Checkpoints while Coding in Jupyter.mp4 (17.33 MB)
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026 Analyzing the Dates from the Initial Data Set.mp4 (40.13 MB)
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027 Extracting the Month Value from the Date Column.mp4 (33.93 MB)
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028 Extracting the Day of the Week from the Date Column.mp4 (19.11 MB)
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030 Analyzing Several Straightforward Columns for this Exercise.mp4 (20.09 MB)
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031 Working on Education, Children, and Pets.mp4 (16.92 MB)
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032 Final Remarks of this Section.mp4 (19.74 MB)
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004 Standardizing the Data.mp4 (15.15 MB)
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005 Splitting the Data for Training and Testing.mp4 (41.89 MB)
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006 Fitting the Model and Assessing its Accuracy.mp4 (35.29 MB)
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008 Interpreting the Coefficients for Our Problem.mp4 (24.77 MB)
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012 Testing the Model We Created.mp4 (31.6 MB)
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002 Deploying the 'absenteeism module' - Part I.mp4 (19.64 MB)
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003 Deploying the 'absenteeism module' - Part II.mp4 (45.15 MB)
MP4
002 Analyzing Age vs Probability in Tableau.mp4 (38.66 MB)
MP4
004 Analyzing Reasons vs Probability in Tableau.mp4 (40.24 MB)
MP4
006 Analyzing Transportation Expense vs Probability in Tableau.mp4 (19.78 MB)
MP4
001 Using the format() Method.mp4 (25.69 MB)
MP4
002 Iterating Over Range Objects.mp4 (12.62 MB)
MP4
003 Introduction to Nested For Loops.mp4 (12.13 MB)
MP4
004 Triple Nested For Loops.mp4 (33 MB)
MP4
005 List Comprehensions.mp4 (43.2 MB)
MP4
006 Anonymous (Lambda) Functions.mp4 (30.34 MB)
MP4
001 Introduction to pandas Series.mp4 (22.21 MB)
MP4
002 Working with Methods in Python - Part I.mp4 (19.55 MB)
MP4
003 Working with Methods in Python - Part II.mp4 (9 MB)
MP4
004 Parameters and Arguments in pandas.mp4 (21.14 MB)
MP4
005 Using unique() and nunique().mp4 (24.29 MB)
MP4
006 Using sort values().mp4 (21.04 MB)
MP4
007 Introduction to pandas DataFrames - Part I.mp4 (10.61 MB)
MP4
008 Introduction to pandas DataFrames - Part II.mp4 (17.83 MB)
MP4
009 pandas DataFrames - Common Attributes.mp4 (29.79 MB)
MP4
010 Data Selection in pandas DataFrames.mp4 (37.26 MB)
MP4
011 pandas DataFrames - Indexing with iloc[].mp4 (32.22 MB)
MP4
012 pandas DataFrames - Indexing with loc[].mp4 (20.69 MB)
MP4
001 An Introduction to Working with Files in Python.mp4 (12.03 MB)
MP4
002 File vs File Object, Reading vs Parsing Data.mp4 (9.42 MB)
MP4
003 Structured, Semi-Structured and Unstructured Data.mp4 (11.07 MB)
MP4
004 Text Files and Data Connectivity.mp4 (10.81 MB)
MP4
005 Importing Data in Python - Principles.mp4 (16.72 MB)
MP4
006 Plain Text Files, Flat Files and More.mp4 (13.16 MB)
MP4
007 Text Files of Fixed Width.mp4 (4.83 MB)
MP4
008 Common Naming Conventions.mp4 (8.21 MB)
MP4
009 Importing Text Files - open().mp4 (28.19 MB)
MP4
010 Importing Text Files - with open().mp4 (26.26 MB)
MP4
011 Importing csv Files - Part I.mp4 (49.87 MB)
MP4
012 Importing csv Files - Part II.mp4 (10.92 MB)
MP4
013 Importing csv Files - Part III.mp4 (75.01 MB)
MP4
014 Importing Data with index col.mp4 (11.63 MB)
MP4
015 Importing Data with loadtxt() and genfromtxt().mp4 (56.33 MB)
MP4
016 Importing Data - Partial Cleaning While Importing Data.mp4 (43.91 MB)
MP4
018 Importing Data from json Files.mp4 (81.95 MB)
MP4
019 An Introduction to Working with Excel Files in Python.mp4 (42.98 MB)
MP4
020 Working with Excel ( xlsx) Data.mp4 (14.41 MB)
MP4
021 Importing Data in Python - an Important Exercise.mp4 (43.01 MB)
MP4
022 Importing Data with the squeeze() Method.mp4 (22.42 MB)
MP4
023 Importing Files in Jupyter.mp4 (19.57 MB)
MP4
024 Saving Your Data with pandas.mp4 (21.06 MB)
MP4
025 Saving Your Data with NumPy - Part I - npy.mp4 (18.91 MB)
MP4
026 Saving Your Data with NumPy - Part II - npz.mp4 (23.26 MB)
MP4
027 Saving Your Data with NumPy - Part III - csv.mp4 (20.83 MB)
MP4
029 Working with Text Files in Python - Conclusion.mp4 (2.11 MB)
MP4
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