Lab Overview Introduction to AI and Machine Learning Machine Learning Process Analytics and Data Sciences The underpinnings of ML Challenges in Machine Learning Project Unsupervised Machine Learning Generalized AI and Real Life Large Projects Project - Forecast Bike Rentals Design & Constructs Machine Learning Prerequisites (Numpy) Introduction to ML Linux Basics Python Project - Churn Emails Project - Churn Emails Inbox with Python Foundations of Python Foundations of Python Project - Predicting Titanic Passenger Survival using Machine Learning and Python Introduction to ML Project - Building Cat vs Non-Cat Image Classifier using NumPy and ANN Project - Introduction to Transfer Learning (Cat vs Non-cats Project) Project - Stock Closing Price Prediction using Deep Learning, TensorFlow2 & Keras Convolutional Neural Networks Artificial Neural Networks - MCQs Training Deep Neural Networks Custom Models and Training with TensorFlow Loading and Preprocessing Data with TensorFlow Natural Language Processing - MCQs Project - How to Build a Neural Network for Image Classification with TensorFlow Project - Training from Scratch vs Transfer Learning Project - Working with Custom Loss Function Project - Image Classification with Pre-trained Keras models Project - Mask R-CNN with OpenCV for Object Detection End-to-End ML Project - California Housing Project - How to Deploy an Image Classification Model using Flask Natural Language Processing Classification Processing Sequences with RNNs and CNNs Autoencoders and GANs End-to-End Machine Learning Project Getting Started with Numpy Getting Started with Pandas ML Prerequisites - Matplotlib End to End Project - Regression (Studio Recorded) End to End Project - Classification (Studio Recorded) Artificial Neural Network Machine Learning Algorithms Training Models MCQs Support Vector Machines MCQs Decision Trees MCQs Ensemble Learning and XGBoost MCQs