•Welcome to the Course
•Introduction to Google Colab
•Links to TensorFlow Notebooks
•Introduction to Artificial Neural Networks ANNs
•The Neuron
•Activation Function
•Cost Function
•Gradient Descent and BackPropagation
•Building the Artificial Neural Networks ANNs
•Step Installation and Setup
•Step Data Preprocessing
•Step Building the Model
•Step Training the Model
•Step Model evaluation and performance
•Binary Classification with Artificial Neural Networks
•Step Binary Classification
•Introduction to Convolutional Neural Networks CNNs
•Convolutional Neural Network Part
•Building Convolutional Neural Networks CNNs
•Building Convolutional Neural Network Step
•CNN for Binary Image Classification
•CNN for Binary Image Classification Step
•Project CNN for Digit Recognition
•CNN for Digit Recognition Part
•Project CNN for Breast Cancer Detection
•CNN for Breast Cancer Detection Part
•Project CNN for Predicting the Bank Customer Satisfaction
•CNN for Predicting the Bank Customer Satisfaction Part
•Project CNN for Credit Card Fraud Detection
•CNN for Credit Card Fraud Detection Part
•Recurrent Neural Networks RNNs
•Introduction to Recurrent Neural Networks
•Vanishing Gradient Problem
•LSTM and GRU
•Project RNN LSTM for IMDB Review Classification
•RNN LSTM for IMDB Review Classification Part
•RNN LSTM for Image Classification
•RNN LSTM for Image Classification Part
•Project Google Stock Price Prediction with RNN and LSTM
•Google Stock Price Prediction with RNN and LSTM Part
•Transfer Learning
•Introduction to Transfer Learning
•Transfer Learning Part
•Natural Language Processing
•Introduction to Natural Language Processing
•NLTK Introduction and Installation
•Tokenization
•Stemming
•Lemmatization
•Stop Words
•POS Tagging
•Chunking
•Named Entity Recognition
•Text Classification Part
•Annex Data Analysis with Numpy
•Numpy Introduction
•NumPy Arrays
•NumPy Arrays Indexing and Selection
•NumPy Operations
•Annex Data Analysis with Pandas
•Pandas Introduction
•Pandas Series
•DataFrames Part
•Multiindex and index hierarchy
•Working with Missing Data
•Groupby Function
•Merging Joining and Concatenating DataFrames
•Pandas Operations
•Reading and Writing Files
•Annex Data Visualization with Matplotlib
•Matplotlib Introduction
•Matplotlib Part
•Welcome to the Course !
•Introduction
•Introduction to Artificial Neural Networks (ANNs)
•Gradient Descent and Back-Propagation
•Building the Artificial Neural Networks (ANNs)
•Step 1 – Installation and Setup
•Step 2 – Data Preprocessing
•Step 3 – Building the Model
•Step 4 – Training the Model
•Step 5 – Model evaluation and performance
•Step 1 – Binary Classification
•Step 2 – Binary Classification
•Step 3 – Binary Classification
•Step 4 – Binary Classification
•Step 5 – Binary Classification
•Introduction to Convolutional Neural Networks (CNNs)
•Convolutional Neural Network Part 1
•Building Convolutional Neural Networks (CNNs)
•Building Convolutional Neural Network Step 1
•Building Convolutional Neural Network Step 2
•Building Convolutional Neural Network Step 3
•Building Convolutional Neural Network Step 4
•Building Convolutional Neural Network Step 5
•CNN for Binary Image Classification Step 1
•CNN for Binary Image Classification Step 2
•CNN for Binary Image Classification Step 3
•CNN for Binary Image Classification Step 4
•CNN for Binary Image Classification Step 5
•Project 1: CNN for Digit Recognition
•CNN for Digit Recognition Part 1
•CNN for Digit Recognition Part 2
•CNN for Digit Recognition Part 3
•Project 2: CNN for Breast Cancer Detection
•CNN for Breast Cancer Detection Part 1
•CNN for Breast Cancer Detection Part 2
•CNN for Breast Cancer Detection Part 3
•Project 3: CNN for Predicting the Bank Customer Satisfaction
•CNN for Predicting the Bank Customer Satisfaction Part 1
•CNN for Predicting the Bank Customer Satisfaction Part 2
•CNN for Predicting the Bank Customer Satisfaction Part 3
•CNN for Predicting the Bank Customer Satisfaction Part 4
•Project 4: CNN for Credit Card Fraud Detection
•CNN for Credit Card Fraud Detection Part 1
•CNN for Credit Card Fraud Detection Part 2
•CNN for Credit Card Fraud Detection Part 3
•CNN for Credit Card Fraud Detection Part 4
•Recurrent Neural Networks (RNNs)
•Project 5: RNN – LSTM for IMDB Review Classification
•RNN – LSTM for IMDB Review Classification Part 1
•RNN – LSTM for IMDB Review Classification Part 2
•RNN – LSTM for IMDB Review Classification Part 3
•RNN – LSTM for Image Classification
•RNN – LSTM for Image Classification Part 1
•RNN – LSTM for Image Classification Part 2
•RNN – LSTM for Image Classification Part 3
•Project 6: Google Stock Price Prediction with RNN and LSTM
•Google Stock Price Prediction with RNN and LSTM Part 1
•Google Stock Price Prediction with RNN and LSTM Part 2
•Google Stock Price Prediction with RNN and LSTM Part 3
•Google Stock Price Prediction with RNN and LSTM Part 4
•Google Stock Price Prediction with RNN and LSTM Part 5
•Transfer Learning Part 1
•Transfer Learning Part 2
•Transfer Learning Part 3
•Transfer Learning Part 4
•Text Classification Part 1
•Text Classification Part 2
•Annex 1: Data Analysis with Numpy
•NumPy Arrays : Indexing and Selection
•Annex 2: Data Analysis with Pandas
•DataFrames Part 1
•DataFrames Part 2
•Multi-index and index hierarchy
•Merging, Joining and Concatenating DataFrames
•Annex 3: Data Visualization with Matplotlib
•Matplotlib Part 1
•Matplotlib Part 2
•Matplotlib Part 3
•Matplotlib Part 4
•Matplotlib Part 5
•Matplotlib Part 6
•Matplotlib Part 7
•Matplotlib Part 8
•Matplotlib Part 9
•Matplotlib Part 10
•