Jupyter notebook

AnacondaConda

Introduction

Google Colab

Solution

PyCharm

Visual Studio Code

Lumber Prices Demand Predictions

A Brief History of Machine Learning

Neural Network Layers

Solution

Numpy and Python Forward Propagation

Explore TensorFlow Tensors

Creating Tensors from Numpy Arrays

Create TensorFlow Tensors

TensorFlow Seeds

Tensor Attributes, Indexing and Expansion

Solution

Tensor Aggregation and Type Casting

Basic Tensor Operations

Matrix Multiplication

Solution Video

The Golden Rule

MatMul's Fruit Stand Use Case

Review Matrix Multiplication

Transpose VS Reshape

Manipulate Tensors

Solution Video

Reshape & Transpose Tensors

Machine Learning Quickstart

Build, Compile, and Train Model Part 1

Build, Compile, and Train Model Part 2

Create Development Environment

What is Regression Analysis

Build a Baseline Regression Model

Build a Neural Network Regression Model

Load Data and Explore Neural Network Architecture

What is Classification

Explore Neural Network Classification in a Browser

Binary Classification

Multi-Class Classification

Generate Linear Data

Evaluation Metrics

Visualize Activation Functions

From Cloud Colab to Local Jupyter

Setting Up a GitHub SSH Key

Starting, Forking, and Cloning Repos

Creating a repository

What is Computer Vision (CV)

Explore How SoftMax works

What is Feature Scaling

Explore the fashion MNIST dataset

Explore Callbacks

Illuminate Convolution & Pooling

Challenge

Perform EDA

Explore the Food 101 dataset on Kaggle

Challenge

Explore the modified ramen sushi dataset

Visualize random images with the labels

Load dataset using ImageDataGenerator

Explore CNNs in a Browser

What is a baseline model

Deep Neural Networks (DNNs)

Convolutional Neural Networks (CNNs)

Part 1 Teachable Machine prototype

Part 2 Acquire and upload images Video B

Part 2 Acquire and upload images

Baseline Model Part 2

Baseline Model

Improvements

CNN Model

Load Dataset and Explore Overfitting

Load Dataset and Explore Overfitting Part 2

Plot Training Curves

Baseline Model from Pseudocode

Explore Classification Types

Food 10 Exploratory Data Analysis

Food 10 Exploratory Data Analysis Part 2

Solution Video 1 Improvements

Solution Video 2 Tuning

Explore Kaggle's Prediction Competition

Load Dataset using ImageDataGenerator

Manipulate Dataset for Model Building

What is Transfer Learning

Feature Extractions Vs Fine-Tuning

What is ImageNet

Bonus Clarification

Reduce and Load Dataset

Custom Callbacks

Load Reduced Dataset Part 2

Load Reduced Dataset

TensorBoard Callbacks

Model Checkpoint Callbacks

Challenge

Early Stopping Callbacks

Solution

Review Transfer Learning, Feature Extraction, and Fine-Tuning

Load Reduced Food 10 Dataset

Explore TensorFlow Hub Pre-Trained Models

Review Feature Extraction, and Fine-Tuning Code Examples

Load Reduced Food 10 Dataset

Apply Data Augmentation

Challenge

Explore TensorFlow Hub and Build a Model From a URL

Apply Data Augmentation Part 2

Compare Feature Extraction to Fine-Tuning

Create ResNet50 Model

Explore and Load Data with ImageDataGenerator

CHALLENGE

Train the Fine-Tuning layers of the model

Explore Transfer Learning Concepts Fine-Tuning

Explore Food 10 Dataset in Three Sizes

Challenge #1

Load Food 10 Dataset from GitHub

Load Images using ImageDataGenerator

Challenge #2 Solution

Challenge #2

Challenge #1 Solution Video

Images, Sound, and Text as Numerical Representations

DevEnv Jupyter Notebook, Conda and Anaconda

Implement Tokenization with TensorFlow

CHALLENGE

Bonus Resource

Large Language Models, NLP Tasks, and Classification

Explore NLP Concepts

Out of Vocabulary Tokens

TextVectorization

Setup Our Development Environment

Padding

CHALLENGE

Solution Video

News Category Dataset

Setup Development Environment and Load Data

Token Sequences, OOV, and Padding Tokenizer

Token Sequences, OOV, and Padding TextVectorization

The Development Environment & Load Dataset

Tokenizer Model

EDA and Tokenizer Hyperparameters

TextVectorization Model

Bonus Video

Setup Development Environment

Tokenization Granularity Context How Many Rs in Strawberry

IMDb Subwords

YELP Tokenization

YELP Model Building

Compare Tokens and Sequences for Deeper Meaning

Compare Tokens and Sequences

Setting Up The Development Environment

Comparing RNNs to LSTMs

Explore Recurrent Neural Network Python Code Examples

Exploring Sequence Problems to Solve (Seq2Seq)

SOLUTION

Build a Generative Shakespearean Sequence Model

Skill Introduction

Setup Your Development Environment

Define and Tokenize Corpus Text

Create and Pad Sequence of Numbers

Create X and y Datasets for Training

One-Hot Encode Categorical Labels

Build, Compile, and Train Model

CHALLENGE

Solution

Exploring RNNs Equation and Memory

Setup The Conda Development Environment

Bidirectional RNN Model Architecture

Explore RNN, Bidirectional RNN, and LSTM

LSTM Model Architecture

Set Up Dev Environment

Bidirectional RNN Model

Single Layer LSTM Model

Bidirectional LSTM Model

Single Layer RNN Model

Single Layer GRU Model

Bidirectional GRU Model

Review Calculus Concepts Gradients and Gradient Descent

Challenge

Solution

Select a Development Environment

Build a Baseline Model

Define, Compile, and Train Model

Data Preprocessing

Explore LSTM, GRU, and LSTMConvolutional Architectures

ConvLSTM Equations and CNNs Explained

Perform Data Preprocessing

Perform EDA on Disaster Tweets

Continue EDA

Solution Video

Set Up the Development Environment

Improve Model Performance for the Disaster Tweets Classifier

Model Performance Experiment

What is Lemma

Set Up Development Environment

Load Dataset and Import Libraries

Preprocess Disaster Dataset

TensorFlow Vector Projector

What is Fine-Tuning

Set Up Development Environment

Build the Custom UseLayer

What is TensorFlow Hub

Solution Videos

Solution Continued

Visualization with Matplotlib

Multivariate Time Series

Univariate Time Series

Trends Visualized

Seasonality & Trends + Seasonality Visualized

Math Concepts Review

What is a Sine Wave, Series, and Why Is It Useful

Build a Synthetic Dataset Dirty Sine Wave

What is Split Time

Data Windowing Concepts

What is the Model Seeing (Behind the Scenes)

Code a Data Windowing Helper Function

Solution Video

Explore Linear Combination Concepts

Why Are We Running Out of Samples

Inside Linear Combinations of DNN & RNN

Solution 1 DNN

Solution 2 RNN

Challenge #1

Challenge #2

Solution #1

Solution #2

Challenge #3

Solution #3

Explore the Sunspots Dataset on Kaggle and Wikipedia

Considering Model Architecture and the 11 or 22 Year Cycles

Compare LSTM and Bidirectional Model Architecture

Why Bidirectional LSTMs are a Poor Fit for Sunspots Predictions

Best of Both Worlds LSTM ❤️ CNN