Practical Machine Learning (2024) --> [ FreeCourseWeb ]
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| Torrent Hash : | 03C27E49CAD93F467D4E31B6EF1AD6FDA0B292A0 |
| Torrent Added : | 3 months ago in Other - Other |
| Torrent Size : | 244.48 MB |
Practical Machine Learning (2024) --> [ FreeCourseWeb ]
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Torrent File Content (31 files)
[ FreeCourseWeb.com ] Practical Machine Learning (2024)
Get Bonus Downloads Here.url -
Get Bonus Downloads Here.url -
183 bytes
~Get Your Files Here !
1. Introduction/1. Introduction.mp4 -
1. Introduction/1. Introduction.mp4 -
18.35 MB
1. Introduction/2. Define the roles and responsibilities of a machine learning engineer.mp4 -
9.57 MB
1. Introduction/3. A day in the life as an ML engineer.html -
123 bytes
1. Introduction/4. Common applications for ML [optional].mp4 -
68.22 MB
1. Introduction/4.1 Good fraud dataset on Kaggle.html -
122 bytes
2. Data Analysis/1. Intro working with datasets to identify key insights.mp4 -
9.85 MB
2. Data Analysis/1.1 Welcome to Colaboratory.html -
102 bytes
2. Data Analysis/2. Getting familiar with some 2020 census data.html -
123 bytes
2. Data Analysis/3. The power of pandas.mp4 -
2.25 MB
2. Data Analysis/3.1 Different ways to use pandas and their performance implications.html -
149 bytes
2. Data Analysis/3.2 L7_ The Power of Pandas.pdf -
54.94 KB
2. Data Analysis/3.3 Pandas Cheat Sheet.html -
109 bytes
2. Data Analysis/3.4 Pandas User Guide.html -
113 bytes
2. Data Analysis/4. Exploring some additional census data.html -
123 bytes
2. Data Analysis/5. Exploring some nba player data.html -
127 bytes
3. Data Pipelines/1. What is an ETL pipeline.mp4 -
6.78 MB
3. Data Pipelines/1.1 L8_ ETLs.pdf -
59.06 KB
3. Data Pipelines/2. Introduction to Airflow [optional].html -
6.41 KB
3. Data Pipelines/2.1 We choose Prefect in place of Airflow for our guided assignment.html -
120 bytes
3. Data Pipelines/3. Introduction to Prefect Creating your first data workflow.html -
127 bytes
3. Data Pipelines/4. Let's migrate our NBA player data exploration into a workflow.html -
127 bytes
4. Train Models/1. Train models using tools from industry like scikit learn and xgboost.mp4 -
16.09 MB
4. Train Models/2. Making predictions off NBA player data.html -
127 bytes
4. Train Models/3. Train a PyTorch neural net model.mp4 -
75.85 MB
4. Train Models/3.1 Colab notebook follow along.html -
146 bytes
5. Deploy Models/1. What is ML in Production.mp4 -
18.03 MB
5. Deploy Models/2. Deploying a PyTorch neural net model.html -
127 bytes
5. Deploy Models/3. Metrics and Monitoring.mp4 -
15.59 MB
6. Outro/1. That's all folks!.mp4 -
3.77 MB
Bonus Resources.txt -
386 bytes
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