Introduction to TensorFlow

Quickstart for beginners

Basic classification: Classify images of clothing

Basic text classification

Text classification with TensorFlow Hub: Movie reviews

Basic regression: Predict fuel efficiency

Overfit and underfit

Save and load models

Load and preprocess images

Load video data

Load CSV data

Load NumPy data

Load a pandas DataFrame

TFRecord and tf.train.Example

Customization basics: tensors and operations

Custom layers

Distributed training with Keras

Distributed training with DTensors

Using DTensors with Keras

Custom training with tf.distribute.Strategy

Multi-worker training with Keras

Custom training loop with Keras and MultiWorkerMirroredStrategy

Parameter server training with ParameterServerStrategy

Save and load a model using a distribution strategy

Computer vision with TensorFlow

Convolutional Neural Network (CNN)

Image classification

Transfer learning and fine-tuning

Transfer learning with TensorFlow Hub

Data augmentation

Image segmentation

Video classification with a 3D convolutional neural network

Simple audio recognition: Recognizing keywords

Transfer learning with YAMNet for environmental sound classification

Classify structured data using Keras preprocessing layers

Classification on imbalanced data

High-performance image generation using Stable Diffusion in KerasCV

Neural style transfer

DeepDream

Deep Convolutional Generative Adversarial Network

pix2pix: Image-to-image translation with a conditional GAN

CycleGAN

Adversarial example using FGSM

Intro to Autoencoders

Convolutional Variational Autoencoder

Integrated gradients

Premade Estimators

Build a linear model with Estimators

Create an Estimator from a Keras model

Multi-worker training with Estimator

Why TensorFlow?

Recommendation systems overview (Building recommendation systems with TensorFlow)

Content-based filtering & collaborative filtering (Building recommendation systems with TensorFlow)

Intro to TensorFlow Recommenders (Building recommendation systems with TensorFlow)

Building a ranking model with TF Recommenders (Building recommendation systems with TensorFlow)

Leveraging context features and multitask learning (Building recommendation systems with TensorFlow)

Deep & Cross Network (Building recommendation systems with TensorFlow)

Efficient serving with ScaNN for retrieval (Building recommendation systems with TensorFlow)

Natural Language Processing - Tokenization (NLP Zero to Hero - Part 1)

Sequencing - Turning sentences into data (NLP Zero to Hero - Part 2)

Training a model to recognize sentiment in text (NLP Zero to Hero - Part 3)

ML with Recurrent Neural Networks (NLP Zero to Hero - Part 4)

Long Short-Term Memory for NLP (NLP Zero to Hero - Part 5)

Training an AI to create poetry (NLP Zero to Hero - Part 6)

Neural Structured Learning - Part 1: Framework overview

Neural Structured Learning - Part 2: Training with natural graphs

Neural Structured Learning - Part 3: Training with synthesized graphs

Neural Structured Learning - Part 4: Adversarial learning for image classification

Announcing TensorFlow 2.0 (Coding TensorFlow)

Distributed Processing and Components (TensorFlow Extended)

Why do I need metadata? (TensorFlow Extended)

How do TFX pipelines work? (TensorFlow Extended)

What exactly is this TFX thing? (TensorFlow Extended)

Get started with using TensorFlow to solve for regression problems (Coding TensorFlow)

Upgrade your existing code for TensorFlow 2.0 (Coding TensorFlow)

How to take advantage of GPUs and TPUs for your ML project (Coding TensorFlow)

Get started with Google Colaboratory (Coding TensorFlow)

Getting Started with TensorFlow in Google Colaboratory (Coding TensorFlow)

Build a deep neural network in 4 mins with TensorFlow in Colab

TensorFlow Lite, Experimental GPU Delegate (Coding TensorFlow)

TensorFlow high-level APIs: Part 1 - loading data

TensorFlow high-level APIs: Part 2 - going deep on data and features

TensorFlow high-level APIs: Part 3 - Building and refining your models

Saving and Loading Models (Coding TensorFlow)

Solve your model’s overfitting and underfitting problems - Pt.1 (Coding TensorFlow)

Solve your model’s overfitting and underfitting problems - Pt.2 (Coding TensorFlow)

Prepare your data for ML | Text Classification Tutorial Pt. 1 (Coding TensorFlow)

Designing a neural network | Text Classification Tutorial Pt. 2 (Coding TensorFlow)

Use TensorFlow to classify clothing images (Coding TensorFlow)

Build a neural network to perform classification | TensorFlow.js (Coding TensorFlow)

Prepare your dataset for machine learning (Coding TensorFlow)

Try TensorFlow.js in your browser (Coding TensorFlow)

TensorFlow Lite for iOS (Coding TensorFlow)

TensorFlow Lite for Android (Coding TensorFlow)

Introducing TensorFlow Lite (Coding TensorFlow)

What’s new in TensorFlow 2.11

Inside TensorFlow: Parameter server training

Inside TensorFlow: TF NumPy

Inside TensorFlow: Building ML infra

Inside TensorFlow: Quantization aware training

Inside TensorFlow: New TF Lite Converter

Inside TensorFlow: TF Debugging

Inside TensorFlow: TF-Agents

Inside TensorFlow: tf.data + tf.distribute

Inside TensorFlow: TF Filesystems

Inside TensorFlow: TF Model Optimization Toolkit (Quantization and Pruning)

Inside TensorFlow: Eager execution runtime

Inside TensorFlow: Control Flow

Inside TensorFlow: tf.data - TF Input Pipeline

Inside TensorFlow: Summaries and TensorBoard

Inside TensorFlow: Resources and Variants

Inside TensorFlow: Functions, not sessions

Inside TensorFlow: tf.distribute.Strategy

Inside TensorFlow: tf.Keras (Part 1)

Inside TensorFlow: tf.Keras (part 2)

Inside TensorFlow: TensorFlow Lite

Inside TensorFlow: AutoGraph