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Natural Language Processing using TensorFlow. Part 1: Tokenization. Part 2: Sequencing. Part 3: Training a model to recognize sentiment in text. Part 4: ML with Recurrent Neural Networks. Part 5: Training an AI to create poetry. Part 6: Learning to write…
Recommendation systems overview (Building recommendation systems with TensorFlow) Content-based filtering & collaborative filtering ( building recommendation systems for Tensorflow) Building a ranking model with TF Recommenders (BuildingRecommendatio…
Recommendation systems overview (Building recommendation systems with TensorFlow).Content-based filtering & collaborative filtering ( building recommendation systems. Natural Language Processing - Tokenization (NLP Zero to Hero - Part 1).Sequencing -…
Inside TensorFlow: New TF Lite Converter.Inside TenseFlow: Quantization aware training. inside Tensorflow: Parameter server training. Inside Tensor Flow: MLIR for TF developers. inside TF-Agents. inside tensorflow.data - TF Input Pipeline.
In this course, you will learn about TensorFlow Extended (TFX). You will learn about ML engineering for production ML deployments with TFX, how TFX pipelines work, why we need metadata, distributed processing and components, model understanding and busin…
Syllabus: Intro Problems with facial recognition Building cyborgs My favorite talk Google Glass Hacking Medical Devices Making Tech Hiring Fair Predicting Career Success Bias Big Social Network Purpose Why Postpartum Depression Building a better person
Syllabus: Introduction What is TensorFlow Lite Benefits Early Access Program Sample App Dependencies Classes Initialization Interpreter API Dependency move model to GPU performance languages support Java support API delegate Optimization Language support
Syllabus: Introduction What are GANs Generator vs Discriminator Neural Networks Deep convolutional Gans Convolutional computation Tensorflow Keras Transposed Convolution Training Loop Generator Loss Code Walkthrough Stable Diffusion Stable Diffusion with…
Syllabus: Introduction Collab Welcome Agenda What is Machine Learning The Data Set Decision Trees Data Labels Training vs Testing Data Good News Training Evaluation Visualizations Tree Accuracy Different Models Free Resources Questions Common Steps Simpl…
Syllabus: Intro What is TensorFlow.js? Open step 2 of codelab Transfer Learning Open step 3 of codelab TensorFlow Hub - base models Open step 4 of codelab Get set up to code Open step 5 of codelab HTML Boilerplate Open step 6 of codelab Add CSS styles Op…
Syllabus: - Introduction - Identifying the problem - What are Keras preprocessing layers - Preprocessing layers that are offered - Transforming inputs from strings to a numeric input - Building a simple model - Adding a new feature - Better per…
Syllabus: - Introduction - User needs & defining success - Mental models - Explainability & trust - Summary and next steps
Syllabus: - Introduction - Intro to federated learning - Mobile keyboards - Making federated learning work in practice - Applying federated learning to mobile keyboards - Where to learn more
Syllabus: - Intro - Encoding text - Language modeling & transformers - Transfer learning & BERT - Conclusion
Syllabus: - Intro - What is Explainable AI? - Interpretable ML methods - Deepdive: Integrated Gradients IG - Picking baselines and future research directions
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