Fundamentals of Data Science Part III

<p><strong>In </strong><strong style=color: rgba(42 181 115 1)>Part III</strong><strong> of this series we cover the fundamentals of machine learning focusing on:</strong></p><ul><li><strong>validation methodology (reprint)</strong></li><li><strong>nearest neighbor <em>k</em>-means support vector machines principal component analysis</strong></li><li><strong>tree-based methods: decision trees bagging random forest boosting XGBoost</strong></li><li><strong>artificial neural networks and deep learning</strong></li><li><strong>reinforcement learning</strong></li></ul><p><strong>The focus is on algorithmic development and programming. We code each technique from scratch in Python using an object-oriented approach. </strong></p><p><br></p><p><br></p>