[Tutorialsplanet NET] Udemy - Beginning with Machine Learning & Data Science in Python
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| Torrent Size : | 542.82 MB |
[Tutorialsplanet NET] Udemy - Beginning with Machine Learning & Data Science in Python
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Torrent File Content (120 files)
[Tutorialsplanet.NET] Udemy - Beginning with Machine Learning & Data Science in Python
1. Working with Machine Learning
1. Exploring Machine Learning and its Types.mp4 -
1. Working with Machine Learning
1. Exploring Machine Learning and its Types.mp4 -
7.33 MB
1. Exploring Machine Learning and its Types.vtt -
5.83 KB
2. Machine Learning Foundations.html -
166 bytes
3. Install Anaconda.mp4 -
8.79 MB
3. Install Anaconda.vtt -
5.56 KB
4. Python Versions.html -
166 bytes
5. Python and Jupyter Demo.mp4 -
17.69 MB
5. Python and Jupyter Demo.vtt -
9.23 KB
5.1 A quick tour of IPython Notebook.zip.zip -
102.82 KB
6. Python Basics.html -
166 bytes
2. Understanding Data Wrangling
1. Introduction.mp4 -
1. Introduction.mp4 -
498.56 KB
1. Introduction.vtt -
281 bytes
10. Summary.mp4 -
539.41 KB
10. Summary.vtt -
396 bytes
2. Reading from a CSV.mp4 -
16.06 MB
2. Reading from a CSV.vtt -
5.86 KB
2.1 Chapter 1 - Reading from a CSV.ipynb.zip.zip -
395.65 KB
2.2 311-service-requests.zip.zip -
8.34 MB
3. Selecting data and finding the most common complaint type.mp4 -
25.11 MB
3. Selecting data and finding the most common complaint type.vtt -
6.63 KB
3.1 Chapter 2 - Selecting data finding the most common complaint type.ipynb.zip.zip -
38.79 KB
4. Which borough has the most noise complaints.mp4 -
19.48 MB
4. Which borough has the most noise complaints.vtt -
6.23 KB
4.1 Chapter 3 - Which borough has the most noise complaints (or, more selecting data).ipynb.zip.zip -
18.11 KB
5. Which weekday do people bike the most.mp4 -
16.96 MB
5. Which weekday do people bike the most.vtt -
5.75 KB
5.1 bikes.csv.csv -
13.48 KB
5.2 Chapter 4 - Find out on which weekday people bike the most with groupby and aggregate.ipynb.zip.zip -
77.77 KB
6. Which month was the snowiest.mp4 -
20.43 MB
6. Which month was the snowiest.vtt -
6.57 KB
6.1 Chapter 5 - String Operations- Which month was the snowiest.ipynb.zip.zip -
78.36 KB
7. Cleaning Messy Data.mp4 -
32.02 MB
7. Cleaning Messy Data.vtt -
9.44 KB
7.1 Chapter 6 - Cleaning up messy data.ipynb.zip.zip -
11.16 KB
8. How to deal with timestamps.mp4 -
16.37 MB
8. How to deal with timestamps.vtt -
4.39 KB
8.1 Chapter 7 - How to deal with timestamps.ipynb.zip.zip -
4.4 KB
8.2 popularity-contest.tsv.tsv -
185.24 KB
9. Loading data from SQL databases.mp4 -
13.45 MB
9. Loading data from SQL databases.vtt -
7.41 KB
9.1 Chapter 8 - Loading data from SQL databases.ipynb.zip.zip -
4.15 KB
9.2 weather_2012_sqlite.zip.zip -
1.39 KB
9.3 weather_2012.csv.csv -
491.96 KB
3. Linear Regression
1. Introduction.mp4 -
1. Introduction.mp4 -
1.73 MB
1. Introduction.vtt -
1.18 KB
10. Model evaluation.mp4 -
10.73 MB
10. Model evaluation.vtt -
4.8 KB
11. Handling categorical features.mp4 -
19.83 MB
11. Handling categorical features.vtt -
8.5 KB
12. Summary.mp4 -
5.46 MB
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