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2.18 GB | 00:24:21 | mp4 | 1920X1080  | 16:9
Genre:eLearning |Language:English


Files Included :
001  Chapter 1  Introduction  (43.44 MB)
002  Chapter 1  Key features of Julia from a data scientist s perspective  (48.05 MB)
003  Chapter 1  Usage scenarios of tools presented in the book  (8.64 MB)
004  Chapter 1  Julia s drawbacks  (15.16 MB)
005  Chapter 1  What data analysis skills will you learn  (3.99 MB)
006  Chapter 1  How can Julia be used for data analysis  (15.62 MB)
007  Chapter 1  Summary  (4.41 MB)
008  Part 1  Essential Julia skills  (5.19 MB)
009  Chapter 2  Getting started with Julia  (31.7 MB)
010  Chapter 2  Defining variables  (15.76 MB)
011  Chapter 2  Using the most important control-flow constructs  (43.65 MB)
012  Chapter 2  Defining functions  (29.47 MB)
013  Chapter 2  Understanding variable scoping rules  (18.58 MB)
014  Chapter 2  Summary  (4.54 MB)
015  Chapter 3  Julia s support for scaling projects  (29.67 MB)
016  Chapter 3  Using multiple dispatch in Julia  (19.68 MB)
017  Chapter 3  Working with packages and modules  (27.49 MB)
018  Chapter 3  Using macros  (20.5 MB)
019  Chapter 3  Summary  (3.98 MB)
020  Chapter 4  Working with collections in Julia  (77.44 MB)
021  Chapter 4  Mapping key-value pairs with dictionaries  (20.41 MB)
022  Chapter 4  Structuring your data by using named tuples  (19.72 MB)
023  Chapter 4  Summary  (4.35 MB)
024  Chapter 5  Advanced topics on handling collections  (52.93 MB)
025  Chapter 5  Defining methods with parametric types  (34.21 MB)
026  Chapter 5  Integrating with Python  (21.44 MB)
027  Chapter 5  Summary  (9.8 MB)
028  Chapter 6  Working with strings  (19.32 MB)
029  Chapter 6  Splitting strings  (12.26 MB)
030  Chapter 6  Using regular expressions to work with strings  (11.41 MB)
031  Chapter 6  Extracting a subset from a string with indexing  (21.13 MB)
032  Chapter 6  Analyzing genre frequency in movies dat  (18.63 MB)
033  Chapter 6  Introducing symbols  (13.53 MB)
034  Chapter 6  Using fixed-width string types to improve performance  (17.62 MB)
035  Chapter 6  Compressing vectors of strings with PooledArrays jl  (19.37 MB)
036  Chapter 6  Choosing appropriate storage for collections of strings  (9.01 MB)
037  Chapter 6  Summary  (17.8 MB)
038  Chapter 7  Handling time-series data and missing values  (45.05 MB)
039  Chapter 7  Working with missing data in Julia  (30.43 MB)
040  Chapter 7  Getting time-series data from the NBP Web API  (16.14 MB)
041  Chapter 7  Analyzing data fetched from the NBP Web API  (29.65 MB)
042  Chapter 7  Summary  (12.06 MB)
043  Part 2  Toolbox for data analysis  (10.62 MB)
044  Chapter 8  First steps with data frames  (46.9 MB)
045  Chapter 8  Loading the data to a data frame  (28.34 MB)
046  Chapter 8  Getting a column out of a data frame  (27.47 MB)
047  Chapter 8  Reading and writing data frames using different formats  (22.4 MB)
048  Chapter 8  Summary  (9.6 MB)
049  Chapter 9  Getting data from a data frame  (72.47 MB)
050  Chapter 9  Analyzing the relationship between puzzle difficulty and popularity  (26.13 MB)
051  Chapter 9  Summary  (9.64 MB)
052  Chapter 10  Creating data frame objects  (76.11 MB)
053  Chapter 10  Creating data frames incrementally  (70.33 MB)
054  Chapter 10  Summary  (12.32 MB)
055  Chapter 11  Converting and grouping data frames  (89.75 MB)
056  Chapter 11  Grouping data frame objects  (46.27 MB)
057  Chapter 11  Summary  (8.76 MB)
058  Chapter 12  Mutating and transforming data frames  (54.95 MB)
059  Chapter 12  Computing additional node features  (33.98 MB)
060  Chapter 12  Using the split-apply-combine approach to predict the developer s type  (52.28 MB)
061  Chapter 12  Reviewing data frame mutation operations  (21.53 MB)
062  Chapter 12  Summary  (14.81 MB)
063  Chapter 13  Advanced transformations of data frames  (56.34 MB)
064  Chapter 13  Investigating the violation column  (24.2 MB)
065  Chapter 13  Preparing data for making predictions  (49.53 MB)
066  Chapter 13  Building a predictive model of arrest probability  (47.99 MB)
067  Chapter 13  Reviewing functionalities provided by DataFrames jl  (17.89 MB)
068  Chapter 13  Summary  (12.8 MB)
069  Chapter 14  Creating web services for sharing data analysis results  (47.81 MB)
070  Chapter 14  Implementing the option pricing simulator  (57.44 MB)
071  Chapter 14  Creating a web service serving the Asian option valuation  (40.14 MB)
072  Chapter 14  Using the Asian option pricing web service  (41.65 MB)
073  Chapter 14  Summary  (13.54 MB)
074  Appendix A  First steps with Julia  (7.71 MB)
075  Appendix A  Getting help in and about Julia  (8.16 MB)
076  Appendix A  Managing packages in Julia  (45.32 MB)
077  Appendix A  Reviewing standard ways to work with Julia  (6.73 MB)
078  Appendix B  Solutions to exercises  (62.87 MB)
079  Appendix C  Julia packages for data science  (11.69 MB)
080  Appendix C  Scaling computing with Julia  (4.99 MB)
081  Appendix C  Working with databases and data storage formats  (8.68 MB)
082  Appendix C  Using data science methods  (8.53 MB)
083  Appendix C  Summary  (3.6 MB)]
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