YouTube Tensorflow Courses List

Dive into the world of scalable machine learning with TensorFlow Extended (TFX)! Explore how to create end-to-end ML pipelines for production-ready models. #TFX #MachineLearning #AIProduction #AIInstitute View all

Dive deep into the world of Deep Learning with TensorFlow! Uncover the revolutionary techniques powering today's AI advancements. #DeepLearning #TensorFlow #AIInstitute View all

Learn the fundamentals of Deep Learning with Tensorflow 20, Keras and Python, and gain the skills to build and deploy powerful AI models with confidence, backed by our proven Problem Promise Proof Proposal methodology. View all

This tutorial provides a comprehensive overview of computer vision using TensorFlow and OpenCV Python. It covers face detection in 5 minutes, pose estimation in 7 minutes at 30 FPS on CPU, hand tracking at 30 FPS on CPU in 5 minutes, and face landmark detection in 5 minutes in real-time using OpenCV Python and MediaPipe. This tutorial is a great resource for anyone looking to learn more about computer vision. View all

Explore the heart of the open-source AI framework that's shaping the future of machine learning and artificial intelligence. #InsideTensorFlow #AI #TensorFlow #Tech View all

Craving coding challenges? Immerse yourself in the world of Coding TensorFlow! From syntax to complex models, empower yourself to create AI magic. #CodingTensorFlow #AIProgramming #Tech View all

Cracking the code with TensorFlow! Learn the ins and outs of coding with TensorFlow and master the art of developing AI applications. #Coding #TensorFlow #AIDevelopment #Tech View all

Learn how to use the TensorFlow Object Detection API to quickly and accurately detect objects in images and videos with this comprehensive online course. View all

This course provides an introduction to TensorFlow and Deep Learning fundamentals with Python. In Part 2, learners will explore non-linearity, building their first neural network with a non-linear activation function. They will also learn about the importance of data pre-processing, the concept of overfitting, and how to use TensorFlow to build a deep learning model. Finally, learners will be able to evaluate their model and make predictions. View all

This course provides an introduction to TensorFlow and Deep Learning fundamentals with Python. It begins with an overview of what deep learning is and why it is used, followed by an explanation of neural networks. It then covers the basics of TensorFlow, including variables, constants, and placeholders. Finally, it provides an introduction to linear regression and how to use it with TensorFlow. View all

This live stream covers the use of TensorFlow.js to create a color classifier. It is divided into seven parts, starting with color classification part 3 and ending with one hot encoding. The classifier is trained to recognize different colors and can be used to classify images. The live stream provides a comprehensive overview of the process and is a great resource for anyone interested in learning about color classification. View all

This course provides an introduction to TensorFlow 2.0, a powerful open source library for machine learning. It covers topics such as installation, Tensor basics, neural networks, linear regression, convolutional neural networks, saving and loading models, functional API, classification projects, transfer learning, recurrent neural networks, natural language processing, and more. Learners will gain the skills to build and deploy machine learning models with TensorFlow 2.0. View all

TensorFlow Lite is a lightweight version of TensorFlow designed for mobile and embedded devices. It offers an interpreter, acceleration with delegates, model conversion with Python, inference with Java, and selective registration with Bazel. It is an ideal choice for on-device machine learning applications. View all

This tutorial introduces the use of TensorFlow Datasets (TFDS) for loading images and text. It compares TFDS to Keras and tf.data, and provides examples of how to use TFDS for loading images and text. It concludes by demonstrating the results of using TFDS for loading data. View all

In this Live Stream, the instructor continued the TensorFlow.js Color Classifier series, covering Parts 8-12. He discussed topics such as creating a color classifier, using the KNN classifier, and creating a color palette. He also held a Tau Day coding challenge, where participants had to create a color classifier. This Live Stream was a great opportunity to learn more about TensorFlow.js and color classification. View all

This tutorial provides a comprehensive guide to using TensorBoard, a visualization tool for TensorFlow. It covers topics such as callbacks, scalars, images, confusion matrices, graphs, HParams, Projector, and TensorFlow Profiler. It is a great resource for anyone looking to get started with TensorBoard and understand its features. View all

This course introduces the Keras architecture and its layers. It explains what a layer does and does not do, and provides examples of the most basic layer and a canonical lazy layer. It also covers nested layers and how to define losses on the fly and collect metrics. Finally, it demonstrates how to use layers in a model. View all

This tutorial provides a beginner-level example of classifying skin cancer using TensorFlow. It begins by introducing the dataset and preprocessing script, then moves on to setting up the model and training it. To improve accuracy, better metrics are introduced, such as the ROC curve. Finally, the tutorial ends with an evaluation and conclusion. View all

This course provides an in-depth look at tf.Keras, a high-level API for building and training models in TensorFlow. It covers topics such as masking, dynamic layers, callbacks, losses and metrics, and use cases. It also explains how to build and train a successful model, and how to use loops for training and inference. View all

This course provides an introduction to Tensorflow Object Detection in 5 hours with Python. It covers installation and setup, collecting images and labelling, training the model, and creating 3 projects. Participants will learn how to clone the baseline code from GitHub, create a virtual environment, collect images using their webcam, and label images for training. By the end of the course, they will have a better understanding of Tensorflow Object Detection and be able to create their own projects. View all

This course teaches participants how to build a deep audio classifier using Python and Tensorflow. It begins with the installation and import of dependencies, followed by the creation of a Tensorflow dataset and the determination of average call length. Participants then build a preprocessing pipeline and a deep learning model, and finally train and evaluate the model. By the end of the course, participants will have a fully functioning deep audio classifier. View all

This tutorial provides an overview of how to create a custom dataset for text using TextLineDataset. It covers how to filter the dataset, create a vocabulary, numericalize with TokenTextEncoder, apply map on datasets, and create a simple model. It also covers how to use the dataset in several files. This tutorial provides a comprehensive guide to creating custom datasets for text. View all

This course provides an introduction to Neural Networks and TensorFlow. It covers how a Neural Network works, loading and looking at data, building a model, making predictions, text classification with movie reviews, and an explanation of the embedding layer. It also covers the Global Average Pooling layer and how to use it to improve accuracy. View all

TensorFlow is a powerful tool for machine learning, and this course explains the differences between using sessions and functions. It explains how variables are used, and how functions can be used to control the flow of data. It also provides a walkthrough of how to use functions to capture, process, and control data. View all

tf.distribute.Strategy is a class with multiple implementations for data parallelism, parameter servers and workers, central storage, mirrored variables, all-reduce algorithms, and one device strategies. It provides a way to parallelize computations across multiple devices, allowing for faster training and inference. View all

Explore the essentials of Python Neural Network Tutorials View all

Get a comprehensive overview of TensorFlow 20 Tutorial - Full Course TensorFlow Tutorial Deep Learning Great Learning View all

Get a comprehensive overview of What is TensorFlow? View all

Explore the essentials of Deep Learning for JavaScript Hackers Use TensorFlowjs in the Browser View all

Get a comprehensive overview of Building recommendation systems with TensorFlow View all

Discover the fundamentals of TensorFlowjs Color Classifier - Intelligence and Learning View all

Discover the fundamentals of TensorFlowjs - Intelligence and Learning View all

Learn the basics of Tensorflow View all

Gain an introduction to Machine Learning with TensorFlow ml5js and Spell View all

Discover the fundamentals of Tensor Processing Units (TPUs) View all

Explore the essentials of Basics of TensorFlow - TF Workshop - Session 1 View all

Get a comprehensive overview of Tensorflow Object Detection (TFOD) View all

Gain an introduction to Lecture 7: Introduction to TensorFlow View all

Discover the fundamentals of TensorFlow Full Course View all