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| [TGx]Downloaded from torrentgalaxy.to .txt |
585B |
| 0 |
460B |
| 0.Importing Data.webm |
9.01MB |
| 0.Welcome.webm |
39.76MB |
| 01. Accessing an API with Python.webm |
32.28MB |
| 01. An Intelligent Spider.webm |
19.85MB |
| 01. Cleaning A Spreadsheet.webm |
35.38MB |
| 01. Complex Relationships.webm |
18.73MB |
| 01. Controlling Conversion.webm |
19.70MB |
| 01. Everyone Loves Charlotte.webm |
27.89MB |
| 01. Examples and Features.webm |
12.81MB |
| 01. Functions.webm |
30.28MB |
| 01. Indexing.webm |
48.99MB |
| 01. Installation and Creating Your First Notebook.webm |
17.66MB |
| 01. Installing scikit-learn using Anaconda.webm |
18.02MB |
| 01. Introducing Tuples.webm |
7.81MB |
| 01. Iterate over Dictionaries.webm |
6.28MB |
| 01. Iteration.webm |
11.04MB |
| 01. Lets Chat About Sequences.webm |
11.60MB |
| 01. Making Better Decisions with Data Analysis.webm |
22.24MB |
| 01. Moving Forward.webm |
4.88MB |
| 01. New Way of Thinking.webm |
55.23MB |
| 01. Numeric.webm |
27.06MB |
| 01. Our Data Set - Flower Power.webm |
19.09MB |
| 01. Packing.webm |
13.49MB |
| 01. Problem Discussion.webm |
13.14MB |
| 01. Project Breakdown.webm |
17.06MB |
| 01. Recap of Functions.webm |
11.44MB |
| 01. Sequence Operations.webm |
7.81MB |
| 01. Summarizing Data Maximum, Minimum, Range.webm |
17.91MB |
| 01. The Application.webm |
18.62MB |
| 01. The Project.webm |
17.47MB |
| 01. Understanding Metrics.webm |
28.73MB |
| 01. Welcome.webm |
46.30MB |
| 01. Welcome.webm |
35.87MB |
| 01. Welcome.webm |
19.16MB |
| 01. Welcome.webm |
16.24MB |
| 01. Welcome to Matplotlib.webm |
13.19MB |
| 01. What Are Objects And Classes.webm |
29.96MB |
| 01. What is a dictionary.webm |
15.55MB |
| 01. What is Anaconda and why use it.webm |
21.77MB |
| 01. What Is Cleaning Data.webm |
16.69MB |
| 01. What is Data Scraping.webm |
31.01MB |
| 01. What is Machine Learning.webm |
22.40MB |
| 01. What Problems Does Netflix Have.webm |
29.49MB |
| 01. Where is it Being Used.webm |
14.11MB |
| 02. Add Items.webm |
10.15MB |
| 02. Boolean Array Indexing.webm |
45.36MB |
| 02. Characteristics of Big Data.webm |
10.04MB |
| 02. Cleaning A Spreadsheet Part 2.webm |
21.28MB |
| 02. Comparing and Combining Dice.webm |
17.75MB |
| 02. Context.webm |
17.35MB |
| 02. Creation.webm |
10.18MB |
| 02. Data is Everywhere.webm |
25.82MB |
| 02. Decision Process.webm |
20.41MB |
| 02. Defining a Function.webm |
3.93MB |
| 02. Defining Terms.webm |
20.44MB |
| 02. Dictionary Syntax and KeyValue Pairs.webm |
12.19MB |
| 02. Functions Recap and Cheat Sheet.md |
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| 02. Gather Information.webm |
12.63MB |
| 02. Gathering Weather Data.webm |
8.34MB |
| 02. Getting Setup.webm |
17.49MB |
| 02. Getting Started with Charting.webm |
10.19MB |
| 02. How Does Netflix Apply Big Data Tools to Solve these Problems.webm |
17.38MB |
| 02. Installing Anaconda.webm |
17.66MB |
| 02. Installing Scrapy.webm |
11.90MB |
| 02. Iterating with Basic For Loops.webm |
8.72MB |
| 02. Labels and Classifiers.webm |
10.90MB |
| 02. Lets Make a Class!.webm |
7.62MB |
| 02. Loading a Dataset.webm |
14.41MB |
| 02. Math.webm |
13.95MB |
| 02. Mutability.webm |
14.51MB |
| 02. Packing, a Practical Example.webm |
5.36MB |
| 02. Packing with Dictionaries.webm |
6.16MB |
| 02. Recap.webm |
8.99MB |
| 02. Returning Values.webm |
24.82MB |
| 02. Running Code in Cells.webm |
12.40MB |
| 02. Running Scripts.webm |
14.24MB |
| 02. Scatter Plot.webm |
17.23MB |
| 02. Scraping APIs.webm |
22.92MB |
| 02. Slices.webm |
6.99MB |
| 02. Strings and Operators.webm |
14.02MB |
| 02. Summarizing Data Mean, Median, Mode.webm |
9.26MB |
| 02. Super-Duper!.webm |
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| 02. Supervised and Unsupervised Learning.webm |
29.39MB |
| 02. Types of Data.webm |
22.40MB |
| 02. Universal Functions.webm |
42.94MB |
| 02. Web Page Anatomy.webm |
18.79MB |
| 03. Accessing Keys and Values.webm |
6.29MB |
| 03. Addition.webm |
13.26MB |
| 03. All About Returns.webm |
8.22MB |
| 03. Analyzing Data Spread.webm |
9.54MB |
| 03. Analyzing the Data.webm |
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| 03. Bad Data Types.webm |
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| 03. Beautiful Soup.webm |
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| 03. Branch and Loop.webm |
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| 03. Calling a Function.webm |
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| 03. Calling the API.webm |
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| 03. Cleaning A CSV.webm |
22.81MB |
| 03. Crawling Spiders.webm |
19.59MB |
| 03. Creating a Spreadsheet.webm |
17.91MB |
| 03. Display the List.webm |
13.87MB |
| 03. Domain Data Storage.webm |
34.58MB |
| 03. Emulating Built-ins.webm |
24.24MB |
| 03. Expecting Exceptions.webm |
18.57MB |
| 03. Giving a Hand.webm |
19.73MB |
| 03. Graphs and Charts.webm |
25.31MB |
| 03. Histogram.webm |
18.01MB |
| 03. Introducing Arrays.webm |
38.46MB |
| 03. Iterating with Enumerate.webm |
7.08MB |
| 03. Len, Min, and Max.webm |
4.42MB |
| 03. Machine Learning Frameworks.webm |
18.93MB |
| 03. Making Predictions with a Classifier.webm |
11.34MB |
| 03. Methods.webm |
14.04MB |
| 03. Multiple Superclasses.webm |
31.27MB |
| 03. Problem Summary and Presentation.webm |
8.88MB |
| 03. Routines in Action.webm |
38.46MB |
| 03. Slicing.webm |
28.20MB |
| 03. Split and Join.webm |
13.41MB |
| 03. String Methods.webm |
13.39MB |
| 03. The Importance of Big Data.webm |
22.77MB |
| 03. The Legend of Charting.webm |
10.76MB |
| 03. The Python Shell.webm |
20.53MB |
| 03. Tuples vs. Lists.md |
2.06KB |
| 03. Unpacking.webm |
4.50MB |
| 03. Unpacking with Dictionaries.md |
1.16KB |
| 03. Using conda to Install Packages.webm |
9.35MB |
| 03. Using Scrapers for Site Testing.webm |
22.21MB |
| 03. Wrapping Up.webm |
27.63MB |
| 04. Arguments and Parameters.webm |
6.65MB |
| 04. Booleans.webm |
17.58MB |
| 04. Box Plot.webm |
14.64MB |
| 04. Chart Types & Reasons to Use.webm |
18.92MB |
| 04. Cleaning A CSV Part 2.webm |
24.40MB |
| 04. Common Issues with Data Scraping.md |
1.67KB |
| 04. Creating the Study Log.webm |
29.11MB |
| 04. Domain Computations.webm |
29.31MB |
| 04. Exploring Our New Problems.webm |
41.33MB |
| 04. Family Tree.webm |
20.08MB |
| 04. Getting Good Data is Hard.webm |
37.57MB |
| 04. Handle Exceptions.webm |
19.96MB |
| 04. Indexing.webm |
31.57MB |
| 04. Is Our Data Normal.webm |
10.71MB |
| 04. Iterating with Ranges.webm |
6.38MB |
| 04. Lets Talk About Scope.webm |
10.96MB |
| 04. Machine Learning Review.webm |
7.79MB |
| 04. Manipulation.webm |
43.46MB |
| 04. Membership Testing.webm |
4.12MB |
| 04. Method Arguments.webm |
13.49MB |
| 04. miniconda.webm |
20.41MB |
| 04. More Soup in the Tureen.webm |
23.56MB |
| 04. Multidimensional Lists.webm |
14.17MB |
| 04. Other Languages.webm |
20.20MB |
| 04. Plotting.webm |
38.74MB |
| 04. Presenting Your Findings.webm |
30.37MB |
| 04. Raising Exceptions.webm |
15.95MB |
| 04. Saving the Data.webm |
22.30MB |
| 04. Subclassing Built-ins.webm |
28.47MB |
| 04. Syntax and Errors.webm |
23.06MB |
| 04. The Endless Web.webm |
38.37MB |
| 04. Tuple Syntax.md |
2.58KB |
| 04. Unpacking, a Practical Example.webm |
5.00MB |
| 04. Update and Mutate Dictionaries.webm |
6.29MB |
| 04. Wrap Up.webm |
6.09MB |
| 04. Yatzy Scoring.webm |
14.14MB |
| 05. Being a Good Citizen.webm |
31.17MB |
| 05. Cleaner Code Through Refactoring.webm |
21.10MB |
| 05. Cleaning A CSV Part 3.webm |
23.96MB |
| 05. Constructicons.webm |
19.30MB |
| 05. Count and Index.webm |
6.86MB |
| 05. Deletion.webm |
14.60MB |
| 05. Design.webm |
31.53MB |
| 05. Domain Infrastructure.webm |
17.49MB |
| 05. Function Gotchas.md |
1.56KB |
| 05. If, Else and Elif.webm |
22.88MB |
| 05. Multidimensional Arrays.webm |
35.33MB |
| 05. No Problem.webm |
17.91MB |
| 05. Saving Your Work.webm |
12.02MB |
| 05. Variables.webm |
20.28MB |
| 05. Visualizing Data.webm |
15.99MB |
| 05. Where to Now.webm |
15.72MB |
| 05. While Loops.webm |
24.61MB |
| 05. Wrapping Up.webm |
7.32MB |
| 06. Charting Our Data Part 1.webm |
9.12MB |
| 06. Cleaning A CSV Part 4.webm |
23.67MB |
| 06. Code Challenges.md |
908B |
| 06. Code Samples Membership Testing, Count, and Index.md |
1.19KB |
| 06. Comparisons.webm |
25.42MB |
| 06. For Loops.webm |
11.23MB |
| 06. Multiple Arguments and Parameters.webm |
5.99MB |
| 06. Special Methods.webm |
19.91MB |
| 06. Wrapping Up.webm |
18.82MB |
| 07. Charting Our Data Part 2.webm |
12.63MB |
| 07. Concatenation and Multiplication.webm |
4.42MB |
| 07. Input and Coding Style.webm |
25.83MB |
| 08. Sequence Operations Cheat Sheet.md |
2.70KB |
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| 2.Combining DataFrames.webm |
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| 3.Meet DataFrames.webm |
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| 3.Until Next Time.webm |
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| 4.Onwards.webm |
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| About This Course.png |
300.66KB |
| Accessing a DataFrame.png |
718.01KB |
| Accessing a Series.png |
680.00KB |
| Beginning Data Science.md |
6.65KB |
| Combining DataFrames.png |
1.21MB |
| Common Issues with Data Scraping.md |
1.67KB |
| Creating a DataFrame.png |
465.05KB |
| Creating a Series.png |
511.47KB |
| Data Analysis Basics.md |
3.91KB |
| Data from APIs.md |
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| Exploration Methods.png |
1.22MB |
| Functions, Packing, and Unpacking.md |
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| Grouping.png |
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| Handling Duplicated and Missing Data.png |
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| intro_matplotlib.zip |
265.59KB |
| intro_matplotlib.zip |
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| intro_matplotlib.zip |
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| Introducing Dictionaries.md |
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| Introducing Lists.md |
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| Introducing Tuples.md |
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| Introduction to Anaconda.md |
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| Introduction to Big Data.md |
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| Introduction to Data Visualization with Matplotlib.md |
4.51KB |
| Introduction to NumPy.md |
4.41KB |
| Jupyter Notebooks.md |
1.24KB |
| Learning SQL.md |
495B |
| Machine Learning Basics.md |
3.36KB |
| Manipulating Text.png |
725.39KB |
| Manipulation Techniques.png |
1.24MB |
| marathon_results_2017.csv |
4.00MB |
| ML-machine-learning-basics.zip |
614B |
| More Visualization.md |
1.01KB |
| Object-Oriented+Python+2.zip |
130.13KB |
| Object-Oriented+Python+2.zip |
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| Object-Oriented+Python+2.zip |
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| Object-Oriented Python.md |
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| Optional Challenge #1 - Top Referrers.png |
393.99KB |
| Optional Challenge #2 - Update Users.png |
399.39KB |
| Optional Challenge #3 - Verified Email List.png |
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| Preparing Data for Analysis.md |
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| preparing-data-for-analysis-student.zip |
38.00KB |
| Python Basics.md |
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| python-introducing-pandas-1.2.0.zip |
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| python-intro-to-numpy.zip |
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| python-intro-to-numpy.zip |
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| python-intro-to-numpy.zip |
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| Python Sequences.md |
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| scraping_data_from_the_web.zip |
37.26KB |
| scraping_data_from_the_web.zip |
37.26KB |
| scraping_data_from_the_web.zip |
37.26KB |
| Scraping Data From the Web.md |
4.08KB |
| Selecting Data.png |
751.58KB |
| Series Vectorization and Broadcasting.png |
553.42KB |
| TutsNode.com.txt |
63B |