Machine Learning | Google for Developers
Send feedback Stay organized with collections Save and categorize content based on your preferences. Google's fast-paced, practical introduction to machine learning, featuring a series of animated videos, interactive visualizations, and hands-on practice exercises. Since 2018, millions of people worldwide have relied on Machine Learning Crash Course to learn how machine learning works, and how mac
Stanford University: Tensorflow for Deep Learning Research
No class on Friday, Feb 2. See syllabus. For the last year's website, visit here TensorFlow is a powerful open-source software library for machine learning developed by researchers at Google. It has many pre-built functions to ease the task of building different neural networks. TensorFlow allows distribution of computation across different computers, as well as multiple CPUs and GPUs within a sin
Stanford CS 224N | Natural Language Processing with Deep Learning
Prerequisites Proficiency in Python All class assignments will be in Python (using NumPy and PyTorch). If you need to remind yourself of Python, or you're not very familiar with NumPy, you can come to the Python review session in week 1 (listed in the schedule). If you have a lot of programming experience but in a different language (e.g. C/C++/Matlab/Java/Javascript), you will probably be fine. C
Stanford University: Tensorflow for Deep Learning Research
No class on Friday, Feb 2. See syllabus. For the last year's website, visit here TensorFlow is a powerful open-source software library for machine learning developed by researchers at Google. It has many pre-built functions to ease the task of building different neural networks. TensorFlow allows distribution of computation across different computers, as well as multiple CPUs and GPUs within a sin
Stanford University: Tensorflow for Deep Learning Research
No class on Friday, Feb 2. See syllabus. For the last year's website, visit here TensorFlow is a powerful open-source software library for machine learning developed by researchers at Google. It has many pre-built functions to ease the task of building different neural networks. TensorFlow allows distribution of computation across different computers, as well as multiple CPUs and GPUs within a sin
第7回TensorFlowと機械学習に必要な数学を基礎から学ぶ会 (2017/03/22 19:30〜)
お知らせ 今回から本勉強会は TensorFlow User Groupとして開催します。 前回までの tensorflow-ja ではありませんのでご注意ください。 概要 機械学習に必要な数学とプログラムを基礎からみっちり初心者向けにおこないます。 Google が作成した Udacity の 深層学習紹介コース を鑑賞して分かるようになることを目指します。 第7回となる今回は新たに15名の方を新規に募ります。 関連する話題についてのライトニングトーク枠もご検討ください。 第1回から第6回までですでに一度でも参加された方で，今回も参加を希望なさる方は無抽選で参加可能です。ただし，参加人数を確認するために出席する旨を主催者までお知らせください。 当日の動画をアップしました！ https://youtu.be/1ullT8HX73U 内容 第7回となる今回は，再帰的ニューラルネットワークに入
Deep Learning | Udacity
Dive into deep learning with this practical course on TensorFlow and the Keras API. Gain an intuitive understanding of neural networks without the dense jargon. Learn to build, train, and optimize your own networks using TensorFlow. The course also introduces transfer learning, leveraging pre-trained models for enhanced performance. Designed for swift proficiency, this course prioritizes hands-on
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GitHub - cs230-stanford/cs230-code-examples: Code examples in pyTorch and Tensorflow for CS230
GitHub - chiphuyen/stanford-tensorflow-tutorials: This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
CSE 258
Machine Learning Training | deepsense.ai
Stanford University: Tensorflow for Deep Learning Research