10最好的TensorFlow教程推荐

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特写 iPhone，显示 Udemy 应用程序和带笔记本的笔记本电脑有数以千计的在线课程和课程可以帮助您提高 TensorFlow 技能并获得 TensorFlow 证书。

在这篇博客文章中，我们的专家汇总了 10 个精选列表 最好的 TensorFlow 课程, 现在在线提供的教程、培训计划、课程和认证。

我们只包括那些符合我们高质量标准的课程。我们花了很多时间和精力来为您收集这些。这些课程适合所有级别的初学者、中级学习者和专家。

以下是这些课程以及它们为您提供的内容！

10最好的TensorFlow教程推荐

课程名 在校生（人数） 评论（计数）
1. Complete Guide to TensorFlow for Deep Learning with Python 我们的最佳选择 92744+ 16491+
2. A Complete Guide on TensorFlow 2.0 using Keras API 52955+ 1827+
3. Complete Tensorflow 2 and Keras Deep Learning Bootcamp 39017+ 6498+
4. TensorFlow Developer Certificate in 2022: Zero to Mastery 34191+ 4562+
5. Android Machine Learning with TensorFlow lite in Java/Kotlin 24261+ 215+
6. Deep Learning with TensorFlow 2.0 [2022] 19626+ 2209+
7. TensorFlow 2.0 Practical 5813+ 646+
8. TensorFlow 2.0 Practical Advanced 5207+ 336+
9. Tensorflow Deep Learning – Data Science in Python 2782+ 242+
10. Deep Learning with TensorFlow 2044+ 237+

1. Complete Guide to TensorFlow for Deep Learning with Python 经过 Jose Portilla Udemy课程 我们的最佳选择

Learn how to use Google’s Deep Learning Framework – TensorFlow with Python! Solve problems with cutting edge techniques!

截至目前，超过 92744+ 人们已经注册了这门课程，而且已经结束了 16491+ 评论.

课程内容
Introduction
Installation and Setup
What is Machine Learning?
Crash Course Overview
Introduction to Neural Networks
TensorFlow Basics
Convolutional Neural Networks
Recurrent Neural Networks
Miscellaneous Topics
AutoEncoders
Reinforcement Learning with OpenAI Gym
GAN – Generative Adversarial Networks
BONUS

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2. A Complete Guide on TensorFlow 2.0 using Keras API 经过 “Hadelin de Ponteves, Ligency I Team, Luka Anicin, Ligency Team” Udemy课程

Build Amazing Applications of Deep Learning and Artificial Intelligence in TensorFlow 2.0

截至目前，超过 52955+ 人们已经注册了这门课程，而且已经结束了 1827+ 评论.

课程内容
Introduction
TensorFlow 2.0 Basics
Artificial Neural Networks
Convolutional Neural Networks
Recurrent Neural Networks
Transfer Learning and Fine Tuning
Deep Reinforcement Learning Theory
Deep Reinforcement Learning for Stock Market trading
Data Validation with TensorFlow Data Validation (TFDV)
Dataset Preprocessing with TensorFlow Transform (TFT)
Fashion API with Flask and TensorFlow 2.0
Image Classification API with TensorFlow Serving
TensorFlow Lite: Prepare a model for a mobile device
Distributed Training with TensorFlow 2.0
Annex 1 – Artificial Neural Networks Theory
Annex 2 – Convolutional Neural Networks Theory
Annex 3 – Recurrent Neural Networks Theory
Bonus Lectures

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3. Complete Tensorflow 2 and Keras Deep Learning Bootcamp 经过 Jose Portilla Udemy课程

Learn to use Python for Deep Learning with Google’s latest Tensorflow 2 library and Keras!

截至目前，超过 39017+ 人们已经注册了这门课程，而且已经结束了 6498+ 评论.

课程内容
“Course Overview, Installs, and Setup
COURSE OVERVIEW CONFIRMATION
NumPy Crash Course
Pandas Crash Course
Visualization Crash Course
Machine Learning Concepts Overview
Basic Artificial Neural Networks – ANNs
Convolutional Neural Networks – CNNs
Recurrent Neural Networks – RNNs
Natural Language Processing
AutoEncoders
Generative Adversarial Networks
Deployment”

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4. TensorFlow Developer Certificate in 2022: Zero to Mastery 经过 “Andrei Neagoie, Daniel Bourke, Zero To Mastery” Udemy课程

“Pass the TensorFlow Developer Certification Exam by Google. Become an AI, Machine Learning, and Deep Learning expert!”

截至目前，超过 34191+ 人们已经注册了这门课程，而且已经结束了 4562+ 评论.

课程内容
Introduction
Deep Learning and TensorFlow Fundamentals
Neural network regression with TensorFlow
Neural network classification in TensorFlow
Computer Vision and Convolutional Neural Networks in TensorFlow
Transfer Learning in TensorFlow Part 1: Feature extraction
Transfer Learning in TensorFlow Part 2: Fine tuning
Transfer Learning with TensorFlow Part 3: Scaling Up
Milestone Project 1: Food Vision Big™
NLP Fundamentals in TensorFlow
Milestone Project 2: SkimLit
Time Series fundamentals in TensorFlow + Milestone Project 3: BitPredict
Passing the TensorFlow Developer Certificate Exam
Where To Go From Here?
Appendix: Machine Learning Primer
Appendix: Machine Learning and Data Science Framework
Appendix: Pandas for Data Analysis
Appendix: NumPy
BONUS SECTION

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5. Android Machine Learning with TensorFlow lite in Java/Kotlin 经过 Hamza Asif Udemy课程

“Learn Machine Learning use in Android using Kotlin Java Android studio and Tensorflow Lite , Build 10+ ML Android Apps”

截至目前，超过 24261+ 人们已经注册了这门课程，而且已经结束了 215+ 评论.

课程内容
Introduction
Setting up the environment
Learning Python
Data Science Libraries
Machine Learning and Deep Learning
Tensorflow
Training First model and creating Android Application
Concrete function and Saved model examples
Predicting Fuel Efficiency of automobiles
Handwritten digits recognition application
Recognition Section
Cats and Dogs Classification
Rock Paper and Scissors Problem
Practice Activity 1 Predict Fitness of a Person
Practice Activity 2 Human and Horses
Bonus

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6. Deep Learning with TensorFlow 2.0 [2022] 经过 “365 Careers, 365 Careers Team” Udemy课程

“Build Deep Learning Algorithms with TensorFlow 2.0, Dive into Neural Networks and Apply Your Skills in a Business Case”

截至目前，超过 19626+ 人们已经注册了这门课程，而且已经结束了 2209+ 评论.

课程内容
Welcome! Course introduction
Introduction to neural networks
Setting up the working environment
Minimal example – your first machine learning algorithm
TensorFlow – An introduction
Going deeper: Introduction to deep neural networks
Backpropagation. A peek into the Mathematics of Optimization
Overfitting
Initialization
Gradient descent and learning rates
Preprocessing
The MNIST example
Business case
Appendix: Linear Algebra Fundamentals
Conclusion
Bonus lecture

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7. TensorFlow 2.0 Practical 经过 “Dr. Ryan Ahmed, Ph.D., MBA, Ligency I Team, Mitchell Bouchard, Ligency Team” Udemy课程

“Master Tensorflow 2.0, Google’s most powerful Machine Learning Library, with 10 practical projects”

截至目前，超过 5813+ 人们已经注册了这门课程，而且已经结束了 646+ 评论.

课程内容
INTRODUCTION AND COURSE OUTLINE
BUILD YOUR FIRST SIMPLE PERCEPTRON (SINGLE NEURON) MODEL IN TF 2.0
BUILD A MULTI LAYER ARTIFICIAL NEURAL NETWORKS FOR REGRESSION TASKS
ARTIFICIAL NEURAL NETWORKS FOR CLASSIFICATION TASKS
DEEP LEARNING FOR IMAGE CLASSIFICATION
MODEL DEPLOYMENT USING TF SERVING

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8. TensorFlow 2.0 Practical Advanced 经过 “Dr. Ryan Ahmed, Ph.D., MBA, Ligency I Team, Mitchell Bouchard, Ligency Team” Udemy课程

“Master Tensorflow 2.0, Google’s most powerful Machine Learning Library, with 5 advanced practical projects”

截至目前，超过 5207+ 人们已经注册了这门课程，而且已经结束了 336+ 评论.

课程内容
INTRODUCTION AND COURSE OUTLINE
REVIEW OF ARTIFICIAL NEURAL NETWORKS AND CONVOLUTIONAL NEURAL NETWORKS
TRANSFER LEARNING (TF HUB)
AUTOENCODERS
DEEP DREAM
GANs
RECURRENT NEURAL NETWORKS (RNNs) AND LSTMs
TENSORFLOW SERVING AND TENSORBOARD

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9. Tensorflow Deep Learning – Data Science in Python 经过 Minerva Singh Udemy课程

Tensorflow Deep Learning Python : Tensorflow Neural Network Training : Tensorflow Models – Android Java : Tensorflow C#

截至目前，超过 2782+ 人们已经注册了这门课程，而且已经结束了 242+ 评论.

课程内容
INTRODUCTION TO TENSORFLOW : The Key Concepts and Software Tools
Introduction to TensorFlow
Other Python Packages and Their Interaction with Tensorflow
Statistical Modelling with Tensorflow
Introduction to Machine Learning
Unsupervised Learning
Supervised Learning
Artificial Neural Networks and Deep Learning with Tensorflow
Convolution Neural Network (CNN) For Image Analysis
Miscellaneous Section

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10. Deep Learning with TensorFlow 经过 Packt Publishing Udemy课程

Channel the power of deep learning with Google’s TensorFlow!

截至目前，超过 2044+ 人们已经注册了这门课程，而且已经结束了 237+ 评论.

课程内容
Getting Started
Deep Neural Networks
Convolutional Neural Networks
Recurrent Neural Networks
Wrapping Up

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下面是一些关于学习的常见问题TensorFlow

学习TensorFlow需要多长时间？

“学习TensorFlow需要多长时间”这个问题的答案是。 . .这取决于。每个人都有不同的需求，每个人都在不同的场景下工作，所以一个人的答案可能与另一个人的答案完全不同。

考虑这些问题：你想学习 TensorFlow 是为了什么？你的出发点在哪里？您是初学者还是有使用 TensorFlow 的经验？你能练习多少？每天1小时？每周40小时？ 查看本课程关于 TensorFlow.

TensorFlow 学起来容易还是难？

不，学习 TensorFlow 对大多数人来说并不难。检查这个 关于如何学习的课程 TensorFlow 立刻！

如何快速学习TensorFlow？

学习 TensorFlow 最快的方法是先得到这个 TensorFlow 课程, 然后尽可能练习你学到的任何东西。即使每天只有 15 分钟的练习。一致性是关键.

在哪里学习 TensorFlow？

如果您想探索和学习 TensorFlow，那么 Udemy 为您提供了学习 TensorFlow 的最佳平台。查看此 关于如何学习的课程 TensorFlow 立刻！