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ml-boost
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ml-boost
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# ml-boost # Week 1: * Study W1 and W2 from [Supervised Machine Learning: Regression and Classification](https://www.coursera.org/learn/machine-learning/) # Week 2: * Study "Car Price Prdiction Project" from [ML Zoomcamp](https://github.com/DataTalksClub/machine-learning-zoomcamp/tree/master/02-regression) * Study W3 from First Course [Supervised Machine Learning: Regression and Classification](https://www.coursera.org/learn/machine-learning/) * Study "Customer Churn Pridction Project" from [ML Zoomcamp](https://github.com/DataTalksClub/machine-learning-zoomcamp/tree/master/03-classification) # Week 3: * Study W1 and W2 of [Advanced Learning Algorithms](https://www.coursera.org/learn/advanced-learning-algorithms/) # Week 4: * Study "Neural Networks and Deep Learning" from [ML Zoomcamp](https://github.com/DataTalksClub/machine-learning-zoomcamp/tree/master/08-deep-learning) # Week 5: * Study W3 of [Advanced Learning Algorithms](https://www.coursera.org/learn/advanced-learning-algorithms/) * Study "Evaluation Metrics" from [ML Zoomcamp](https://github.com/DataTalksClub/machine-learning-zoomcamp/tree/master/04-evaluation) # Week 6: * Study W4 of [Advanced Learning Algorithms](https://www.coursera.org/learn/advanced-learning-algorithms/) * Study "Decision Trees & XGBoost" & " Credit risk scoring project" from [ML Zoomcamp](https://github.com/DataTalksClub/machine-learning-zoomcamp/tree/master/06-trees) # Week 7: * Study W1 and W2 of [Unsupervised Learning, Recommenders, Reinforcement Learning](https://www.coursera.org/learn/unsupervised-learning-recommenders-reinforcement-learning) # Week 8: * Study W3 of [Unsupervised Learning, Recommenders, Reinforcement Learning](https://www.coursera.org/learn/unsupervised-learning-recommenders-reinforcement-learning)
