TensorFlow

TensorFlow

TensorFlow In 5 Minutes

In this video by Simplilearn, covers *TensorFlow In 5 Minutes*.

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Databricks TensorFlow

Quick to Production with Minimal MLOps with the Best of Spark and TensorFlow

In this session, learn how we can get deep learning and ml models with TensorFlow into production quickly right after prototyping. Using TensorFlow with big datasets in a distributed setting has been an issue for small teams like ours due to complicated MLOps code, but with what we cover in the talk, we could now […]

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Computer Vision TensorFlow

Tensorflow Object Detection in 5 Hours with Python

Want to get up to speed on AI powered Object Detection but not sure where to start? Want to start building your own deep learning Object Detection models? This is the course you need! In this course, you’ll learn everything you need to know to go from beginner to practitioner when it comes to deep […]

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Computer Vision Raspberry Pi TensorFlow

Introduction to object detection on Raspberry Pi

In the first episode of Machine Learning for Raspberry Pi, learn how to download a pre-trained TensorFlow Lite object detection model and deploy it to your Raspberry Pi. This model can be used to recognize general objects such as an apple, a television, or a car.

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Javascript TensorFlow

Finishing the Tensorflow.js Autoencoder project

The Coding Train wraps up his series on the TensorFlow.js autoencoder.

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Machine Learning TensorFlow

Keras Full Course for Beginners

Keras is a high-level, deep learning API developed by Google for implementing neural networks. Written in Python, it is used to make the implementation of neural networks easy. Keras is relatively easy to learn and work with because it provides a python frontend with a high level of abstraction while having the option of multiple […]

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Natural Language Processing TensorFlow

Text Classification Using BERT & Tensorflow

Using BERT and Tensorflow 2.0, we will write simple code to classify emails as spam or not spam. BERT will be used to generate sentence encoding for all emails and after that we will use a simple neural network with one drop out layer and one output layer.

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University of Tübingen Researchers Open-Source ‘CARLA’, A Python Library for Benchmarking Counterfactual Explanation Methods Across Data Sets and Machine Learning Models
AI Python TensorFlow

‘CARLA’ Python Library for Benchmarking Counterfactual Explanation Methods Across Data Sets and Machine Learning Models

Researchers at the University of Tübingen are unveiling a new python library CARLA (Counterfactual And Recourse LibrAry) which will allow for benchmarking counterfactual explanation methods across different data sets and machines. CARLA is an innovative open-source library that allows researchers to benchmark predictive counterfactual explanation and recourse CE methods for managing uncertainty in their analyses. […]

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TensorFlow

How to make TensorFlow models run faster on GPUs

XLA compilation on GPU can greatly boost the performance of your models, Learn how to use @tf.function(jit_compile=True) in TensorFlow to control what exact scopes are being compiled, and how to debug the performance of the resulting program. We’ll cover writing compiled models, debugging them, and exploring the performance characteristics and optimizations the XLA compiler performs, […]

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