WHAT YOU WILL LEARN
Build ML models with NumPy & scikit-learn, build & train supervised models for prediction & binary classification tasks (linear, logistic regression)

Build & train a neural network with TensorFlow to perform multi-class classification, & build & use decision trees & tree ensemble methods

Apply best practices for ML development & use unsupervised learning techniques for unsupervised learning including clustering & anomaly detection

Build recommender systems with a collaborative filtering approach & a content-based deep learning method & build a deep reinforcement learning model

SKILLS YOU WILL GAIN
Decision Trees
Artificial Neural Network
Logistic Regression
Recommender Systems
Linear Regression
Regularization to Avoid Overfitting
Gradient Descent
Supervised Learning
Logistic Regression for Classification
Xgboost
Tensorflow
Tree Ensembles