download скачать Free download скачать : Udemy One Week of Data Science in Python New 2024
mp4 | Video: h264,1280X720 | Audio: AAC, 44.1 KHz
Genre:eLearning | Language: English | Size:8.24 GB

Files Included :

1  Course Welcome Message.mp4 (24.73 MB)
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1 1 0  Course Intro and Data Science Starter Pack.zip (8.62 MB)
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2  Introduction, Best Practices, & Success Tips.mp4 (118.44 MB)
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3  Course Outline.mp4 (32.92 MB)
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4  What is Data Science.mp4 (162.35 MB)
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5  What is a Typical Data Scientist Profile, Education, Experience & Salary.mp4 (224.32 MB)
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6  What do Data Scientists REALLY do.mp4 (47.46 MB)
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7  What do Recruiters Look for in Data Science Applicants.mp4 (74.45 MB)
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8  What Data Science Jobs are Available Out there.mp4 (165.43 MB)
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1  Bias Variance Tradeoff.mp4 (202.8 MB)
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2  L2 regularization (Ridge).mp4 (125.11 MB)
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3  L1 regularization (Lasso).mp4 (93.42 MB)
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1  Day #1 Welcome Message.mp4 (30.21 MB)
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1 1 Data Wangling, EDA and Feature Engineering.zip (2.9 MB)
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10  Coding Task #4 - Perform Feature Scaling Normalization & Standardization.mp4 (20.37 MB)
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11  Exercise #4 [Optional].mp4 (25.82 MB)
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12  Coding Task #5 - Perform Filtering Operation.mp4 (59.64 MB)
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13  Exercise #5 [Optional].mp4 (20.48 MB)
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14  Coding Task #6 - Perform EDA on Both Classes.mp4 (40.11 MB)
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15  Exercise #6 [Optional].mp4 (29.29 MB)
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16  Coding Task #7 - Functions With Pandas.mp4 (44.59 MB)
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17  Exercise #7 [Optional].mp4 (30.51 MB)
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18  Coding Task #8 - Correlations and Histograms.mp4 (58.64 MB)
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19  Exercise #8 [Optional].mp4 (31.12 MB)
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2  Project Introduction & Data Wrangling 101.mp4 (95.83 MB)
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20  Final Capstone Project Overview.mp4 (32.85 MB)
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21  Final Capstone Project Solution.mp4 (94.41 MB)
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22  Day #1 Conclusion.mp4 (4.26 MB)
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3  Coding Task #1 - Import Data and Obtain Data Statistical Summary.mp4 (120.81 MB)
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4  Exercise #1 [Optional].mp4 (27.53 MB)
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5  Coding Task #2 - Deal with Missing Values.mp4 (74.95 MB)
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6  Exercise #2 [Optional].mp4 (30.28 MB)
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7  Coding Task #3 - Perform One-Hot Encoding.mp4 (40.16 MB)
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8  Exercise #3 [Optional].mp4 (27.46 MB)
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9  Feature Scaling 101.mp4 (79.84 MB)
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1  Day #2 Welcome Message.mp4 (23.1 MB)
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1 1 Effective Data Visualization in Data Science.zip (3.11 MB)
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10  Coding Task #4 - Plot Histograms.mp4 (28.52 MB)
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11  Exercise #4 [Optional].mp4 (38.48 MB)
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12  Coding Task #5 - Searborn Part 1.mp4 (67.09 MB)
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13  Exercise #5 [Optional].mp4 (13.28 MB)
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14  Coding Task #6 - Searborn Part 2.mp4 (75.01 MB)
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15  Exercise #6 [Optional].mp4 (50.16 MB)
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16  Final Capstone Project Overview.mp4 (41.38 MB)
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17  Final Capstone Project Solution.mp4 (117.76 MB)
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18  Day #2 Conclusion.mp4 (3.99 MB)
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2  Project Overview and Key Learning Outcomes.mp4 (81.01 MB)
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3  Data Visualization 101.mp4 (83.87 MB)
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4  Coding Task #1 - Plot Pie Charts with Matplotlib.mp4 (73.37 MB)
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5  Exercise #1 [Optional].mp4 (41.23 MB)
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6  Coding Task #2 - Plot Single & Multiple LinePlots.mp4 (53.34 MB)
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7  Exercise #2 [Optional].mp4 (23.41 MB)
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8  Coding Task #3 - Plot Scatterplots.mp4 (30.05 MB)
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9  Exercise #3 [Optional].mp4 (19.85 MB)
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1  Day #3 Welcome Message.mp4 (33.5 MB)
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1 2 Regression Analysis in DS.zip (8.2 MB)
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10  Exercise #3 [Optional].mp4 (29.59 MB)
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11  Coding Task #4 - Train an XG-Boost Model.mp4 (52.72 MB)
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12  Exercise #4 [Optional].mp4 (17.23 MB)
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13  Final Capstone Project Overview.mp4 (24.57 MB)
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14  Final Capstone Project Solution.mp4 (130 MB)
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15  Day #3 Conclusion.mp4 (5.71 MB)
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2  Project Overview and Key Learning Outcomes.mp4 (91.58 MB)
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3  What is Regression.mp4 (43.77 MB)
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4  What is XGBoost and Why.mp4 (48.44 MB)
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5  Coding Task #1 - Import Libraries and Datasets.mp4 (43.06 MB)
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6  Exercise #1 [Optional].mp4 (15.21 MB)
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7  Coding Task #2 - Exploratory Data Analysis (EDA) & Visualization.mp4 (54.51 MB)
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8  Exercise #2 [Optional].mp4 (24.3 MB)
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9  Coding Task #3 - Prepare The Data Before Model Training.mp4 (19.67 MB)
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1  Day #4 Welcome Message.mp4 (30.39 MB)
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1 1 Classification in DS.zip (6.07 MB)
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10  Exercise #3 [Optional].mp4 (27.44 MB)
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11  Coding Task #5 - Train & Evaluate Support Vector Machines.mp4 (67.56 MB)
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12  Coding Task #6 - Train & Evaluate Random Forest Classifier Model.mp4 (55.85 MB)
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13  Coding Task #7 - Train & Evaluate K-Nearest Neighbors Classifier.mp4 (67.13 MB)
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14  Exercise #4 [Optional].mp4 (14.22 MB)
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15  Coding Task #8 - Train & Evaluate a Naïve Bayes Classifier Model.mp4 (108.97 MB)
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16  Exercise #5 [Optional].mp4 (39.16 MB)
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17  Coding Task #9 - Compare Classifier Models.mp4 (52.14 MB)
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18  Coding Task #10 - Concluding Remarks.mp4 (18.01 MB)
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19  Final Capstone Project.mp4 (35.44 MB)
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2  Introduction & Project Overview.mp4 (62.68 MB)
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20  Final Capstone Project Solution Part #1.mp4 (74.96 MB)
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21  Final Capstone Project Solution Part #2.mp4 (44.38 MB)
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22  Final Capstone Project Solution Part #3.mp4 (27.5 MB)
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23  Day #4 Conclusion.mp4 (4.17 MB)
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3  Classification Models KPIs.mp4 (171.02 MB)
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4  Coding Task #1 - Import Libraries and Datasets.mp4 (51.26 MB)
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5  Exercise #1  [Optional].mp4 (33.14 MB)
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6  Coding Task #2 - Perform Data Visualization.mp4 (93.69 MB)
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7  Exercise #2 [Optional].mp4 (40.35 MB)
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8  Coding Task #3 - Plot Feature Importance.mp4 (61.23 MB)
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9  Coding Task #4 - Train & Evaluate a Logistic Regression Classifier Model.mp4 (54.08 MB)
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1  Day #5 Welcome Message.mp4 (36.83 MB)
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1 1 Data Science on Autopilot.zip (1.99 MB)
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10  Coding Task #4 - Train Regression Models on Autopilot.mp4 (77.6 MB)
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11  Coding Task #5 - Evaluate Trained Regression Models.mp4 (63.81 MB)
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12  Exercise #4 [Optional].mp4 (55.34 MB)
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13  Final Capstone Project Overview.mp4 (26.3 MB)
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14  Final Capstone Project Solution.mp4 (110.29 MB)
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15  Day #5 Conclusion.mp4 (5.88 MB)
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2  Introduction and Project Overview.mp4 (67.6 MB)
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3  What is AutoGluon.mp4 (164.47 MB)
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4  Coding Task #1 - Import AutoGluon, Key Libraries & Datasets.mp4 (67.97 MB)
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5  Exercise #1 [Optional].mp4 (13.59 MB)
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6  Coding Task #2 - Perform Exploratory Data Analysis (EDA).mp4 (42.37 MB)
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7  Exercise #2 [Optional].mp4 (22.74 MB)
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8  Coding Task #3 - Perform Data Visualization.mp4 (46.9 MB)
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9  Exercise #3 [Optional].mp4 (16.72 MB)
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1  Day #6 Welcome Message.mp4 (27.21 MB)
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1 2 Models Optimization.zip (2.65 MB)
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10  Coding Task #4 - Prepare the Data Before Model Training.mp4 (51.02 MB)
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11  Coding Task #5 - Train an XG-Boost Algorithm (Without Optimization).mp4 (48.92 MB)
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12  Exercise #3 [Optional].mp4 (26.57 MB)
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13  Coding Task #6 - GridSearchCV Optimization.mp4 (79.77 MB)
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14  Exercise #4 [Optional].mp4 (52.85 MB)
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15  Coding Task #7 - Random Search Optimization.mp4 (41.09 MB)
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16  Coding Task #8 - Bayesian Search Optimization.mp4 (43.85 MB)
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17  Final Capstone Project Question.mp4 (19.4 MB)
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18  Final Capstone Project Solution.mp4 (68.85 MB)
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19  Day #6 Conclusion.mp4 (4.12 MB)
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2  Project Overview.mp4 (87.19 MB)
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3  Hyperparameters 101.mp4 (95.58 MB)
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4  Optimization Strategies.mp4 (126.74 MB)
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5  Coding Task #1 - Import Libraries and Datasets.mp4 (42.77 MB)
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6  Exercise #1 [Optional].mp4 (21.5 MB)
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7  Coding Task #2 - Perform Data Cleaning.mp4 (60.73 MB)
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8  Coding Task #3 - Perform Data Visualization.mp4 (69.01 MB)
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9  Exercise #2 [Optional].mp4 (22.26 MB)
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1  Task #1  Project Overview.mp4 (74.53 MB)
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1 1 Deep Learning.zip (135.88 MB)
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2  Task #2  Upload and Explore the Data.mp4 (64.8 MB)
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3  Task #3  Train Deep Neural Network Model.mp4 (47.41 MB)
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4  Task #4  Explainable AI and Model Understanding.mp4 (176.81 MB)
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1  Regression Math.mp4 (92.9 MB)
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2  Least Sum of Squares.mp4 (140.47 MB)
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3  Scikit Learn.mp4 (100.29 MB)
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4  XG-Boost Fundaments.mp4 (366.37 MB)
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5  XG-Boost Deep Dive.mp4 (101.51 MB)
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6  What is Boosting.mp4 (128.34 MB)
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7  Ensemble Learning.mp4 (142.9 MB)
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