Introduction

This repository contains all my work for Machine Learning and Deep Learning Specialization on Coursera.

Certications:

• Machine Learning
• Structuring Machine Learning Projects
• Neural Networks and Deep Learning
• Improving Deep Neural Networks: Hyperparameter tuning, Recognition and Optimization
• Convolutional Neural Networks

If there is any problems regarding jupyter notebook loading on github, copy paste the link to jupyter notebook nbviewer.

Personal Notes

You can find my personal notes on my website

Lab Assignments

Machine Learning

• Week 2 - LA 1 - Linear Regression
• Week 3 - LA 2 - Logistic Regression
• Week 4 - LA 3 - Multi-class Classification and Neural Networks
• Week 5 - LA 4 - Neural Networks Learning
• Week 6 - LA 5 - Regularized Linear Regression and Bias v.s. Variance
• Week 7 - LA 6 - Support Vector Machines
• Week 8 - LA 7 - K-means Clustering and Principal Component Analysis
• Week 9 - LA 8 - Anomaly Detection and Recommender Systems

Deep Learning Specialization

• Neural Networks and Deep Learning

  • Week 2 - LA 1 - Logistic Regression with a Neural Network mindset
  • Week 3 - LA 2 - Planar data classification with one hidden layer
  • Week 4 - LA 3 - Building your Deep Neural Network: Step by Step
  • Week 4 - LA 4 - Deep Neural Network for Image Classification: Application

• Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

  • Week 1 - LA 1 - Initialization
  • Week 1 - LA 2 - Regularization
  • Week 1 - LA 3 - Gradient Checking
  • Week 2 - LA 4 - Optimization Methods
  • Week 3 - LA 5 - TensorFlow Tutorial

• Convolutional Neural Networks

  • Week 1 - LA 1 - Convolutional Model: step by step
  • Week 1 - LA 2 - Convolutional Model: application
  • Week 2 - LA 3 - Keras - Tutorial
  • Week 2 - LA 4 - Residual Networks
  • Week 3 - LA 5 - Car detection with YOLO
  • Week 4 - LA 6 - Art generation with Neural Style Transfer
  • Week 4 - LA 7 - Face Recognition