TensorFlow Tutorial | TensorFlow in a Nutshell

TensorFlow is an open source framework developed by Google researchers to run machine learning, deep learning and other statistical and predictive analytics workloads. Like similar platforms, it's designed to streamline the process of developing and executing advanced analytics applications for users such as data scientists, statisticians and predictive modelers.

Kubeflow AI + Amazon SageMaker + EKS Workshop

In this workshop, we build real-world machine learning pipelines using TensorFlow Extended (TFX), KubeFlow, Airflow, and MLflow.

How to Build Object Detection APIs Using TensorFlow and Flask

Learn how to build Object Detection APIs through deploying a Flask application that runs TensorFlow. This video will show how to create two different REST APIs that will allow you to detect 80 different classes within images. This tutorial is great at demonstrating how to build APIs that could be used for a Web or Mobile application to run object detections.

TensorFlow.js | Bringing ML and Linear Algebra to Node.js

No Python required - this session will highlight unique opportunities by bringing ML and linear algebra to Node.js with TensorFlow.js. Nick will highlight how you can get started using pre-trained models, train your own models, and run TensorFlow.js in various Node.js environments (server, IoT).

Automatic Text Generation using TensorFlow, Keras and LSTM

In this lesson, I will show how to use LSTM to generate text sequences on given seed text. Please like and subscribe to this channel to show your support.

Top 10 Machine Learning Frameworks for Web Development

Top 10 Machine Learning Frameworks for Web Development. There are many machine learning framework used for the web development company. The web development with machine learning is going to change the IT world in the future as it is becoming popular day by day. These frameworks are written in different languages such as Python, Java, C++, Scala, etc.

How to Categorize TensorFlow.js Images Made easy

TensorFlow.js Image Classification Made Easy In this video you're going to discover an easy way how to train a convolutional neural network for image classification and use the created TensorFlow.js image classifier afterwards to score x-ray images locally in your web browser.

Understanding Eager Execution Runtime in TensorFlow

In this TensorFlow tutorial, you'll understand Eager execution runtime in TensorFlow. TensorFlow's eager execution is an imperative programming environment that evaluates operations immediately, without building graphs. Eager execution supports most TensorFlow operations and GPU acceleration. Eager execution is a flexible machine learning platform for research and experimentation

Build a Deep Audio De-Noiser Using TensorFlow 2.0

Build a Deep Audio De-Noiser Using TensorFlow 2.0 .Speech denoising is a long-standing problem. Given a noisy input signal, the aim is to filter out such noise without degrading the signal of interest.

Everything you need to know about TensorFlow

In this TensorFlow full course tutorial for Beginners will help you learn about Deep Learning with TensorFlow in detail, understand the basics of Deep Learning, how to install TensorFlow 2.0 on Ubuntu, how to use TensorFlow in Python, how to use TensorFlow object detection API to detect objects in images as well as videos

Graph Rewriting for Functions in TensorFlow 2.0

On this episode of TensorFlow Tutorial, Software Engineer Eugene Zhulenev demonstrates graph rewriting for functions in TensorFlow 2.0. Take an inside look into the TensorFlow team’s own internal training sessions--technical deep dives into TensorFlow by the very people who are building it!

Predicting the Stock price Using TensorFlow

Predicting the Stock price Using TensorFlow. A simple deep learning model for stock price prediction using TensorFlow

Multi-level Intermediate Representation compiler for TensorFlow Developers

On this episode of Inside TensorFlow, Software Engineer Jacques Pienaar discusses MLIR: multi-level intermediate representation compiler infrastructure for TensorFlow developers.

How to Program UMAP from Scratch

How to Program UMAP from Scratch. And how to improve UMAP. Continue reading on Towards Data Science

Easy Image Classification with TensorFlow 2.0

Easy Image Classification with TensorFlow 2.0 ... Eager execution is enabled by default, without sacrificing the performance optimizations of graph-based execution. APIs are ... Tighter Keras integration as the high-level API.

TensorFlow 2.0: Natural Language Processing

NLP in TensorFlow 2.0/PyTorch.This blog post is dedicated to the use of the Transformers library using TensorFlow: using the Keras API as well as the TensorFlow TPUStrategy to fine-tune a State-of-The-Art Transformer model.