Supervised Learning for AI with Python and Tensorflow 2

Description

Acquire a deep understanding of Supervised Learning methods by finding out the basics and implementing them in NumPy.

Acquire hands-on expertise utilizing in style Deep Learning frameworks resembling Tensorflow 2 and Keras.

Part 1 – The Fundamentals:

– Study what Supervised Learning is, within the context of AI

– Study the distinction between Parametric and non-Parametric fashions

– Study the basics: Weights and biases, threshold capabilities and studying charges

– An introduction to the Vectorization approach to assist pace up our self carried out code

– Study to course of actual information: Characteristic Scaling, Splitting Knowledge, One-hot Encoding and Dealing with lacking information

– Classification vs Regression

Part 2 – Feedforward Networks:

– Study concerning the Gradient Descent optimization algorithm.

– Implement the Logistic Regression mannequin utilizing NumPy

– Implement a Feedforward Community utilizing NumPy

– Study the distinction between Multi-task and Multi-class Classification

– Perceive the Vanishing Gradient Downside

– Overfitting

– Batching and numerous Optimizers (Momentum, RMSprop, Adam)

Part 3 – Convolutional Neural Networks:

– Fundamentals resembling filters, padding, strides and reshaping

– Implement a Convolutional Neural Community utilizing NumPy

– Introduction to Tensorfow 2 and Keras

– Knowledge Augmentation to cut back overfitting

– Perceive and implement Switch Learning to require much less information

– Analyse Object Classification fashions utilizing Occlusion Sensitivity

– Generate Artwork utilizing Type Switch

– One-Shot Learning for Face Verification and Face Recognition

– Carry out Object Detection for Blood Stream pictures

Part 4 – Sequential Knowledge

– Perceive Sequential Knowledge and when information must be modeled as Sequential Knowledge

– Implement a Recurrent Neural Community utilizing NumPy

– Implement LSTM and GRUs in Tensorflow 2/Keras

– Sentiment Classification from the fundamentals to the extra superior methods

– Perceive Phrase Embeddings

– Generate textual content much like Romeo and Juliet

– Implement an Consideration Mannequin utilizing Tensorflow 2/Keras