Deep Learning Specialization
Published:
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Course 1: Supervised Learning: Regression and Classification
- Topics Covered: Classification & Regression machine learning problems, over & under fitting, gradient descent, MSE, MAE and logistic loss functions, Regularization, Polynomial Regression & Feature Maps
- Projects & Code: Here
Course 2: Advanced Learning Algorithms
- Topics Covered: Neural Networks (ANNs), forward and backward propagation (Training ANNs), Activation functions, and Decision Trees, Multi-Class Classification, Xgboost
- Projects & Code: Here
Course 3: Unsupervised Learning, Recommenders, Reinforcement Learning
- Topics Covered: Unsupervised Learning Algorithms, Dimensionality Reduction with PCA, K-Means Clustering, Anomaly Detection, Building Recommendation Systems, Deep Reinforcement Learning Models
- Projects & Code: Here