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60 Days of Data Science and Machine Learning
Hello, everyone.
Following are third week of this series. You can find them on my github repository. You can run all the notebook on colab or jupyter as well.
Topic : Support Vector Regression, Decision Tree Regression and Random Forest Regression
Day 17 - Kaggle's Annual Machine Learning and Data Science Survey Part1
Topic : Data Cleaning, Preprocessing, EDA and etc
Day 18 - DecisionTreeRegressor and RandomForestRegressor
Topic : Implement Regressor with Decision Tree and Random Forest
Day 19 - Kaggle's Annual Machine Learning and Data Science Survey Part2
Topic : Data Cleaning, Preprocessing, EDA and etc
Day 20 - Detailed Crypto Analysis
Topic : Basic intuition to buid model to predict
Day 21 - Detailed Analysis of the Netflix Content
Topic : Detailed analysis of the Netflix Content
Hope my work would be little bit helpful for AI enthusiastic.
If that, please star that repository then follow me on Github and Dev.to
https://github.com/thunderstroke325
https://dev.to/thunderstroke
Best Regards.
Original Link: https://dev.to/thunderstroke/60-days-of-data-science-and-machine-learning-1740
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