11 Best Tensorflow Courses & Tutorials - Learn Tensorflow Online
Highly curated the best Tensorflow tutorials for beginners. Start with the top Tensorflow tutorials and learn Tensorflow as beginners.
TensorFlow tutorials Coursera is an open-source library that is commonly used for data flow programming. However, it also includes a symbolic math library that can be used for machine learning applications and neural networking.
Developed by the Google Brain team, TensorFlow tutorials Coursera is already playing a huge role in helping machines advance. This is why it is one of the most important technologies that people should definitely learn to advance their careers. It is used by major companies all over the world, including Airbnb, eBay, Dropbox, Snapchat, Twitter, Uber, SAP, Qualcomm, IBM, Intel, and of course, Google!
Disclosure: Coursesity is supported by the learners community. We may earn an affiliate commission when you make a purchase via links on Coursesity.
Top Tensorflow Classes, Courses Certifications List
- Complete Guide to TensorFlow for Deep Learning with Python
- Master Deep Learning with TensorFlow in Python
- Modern Deep Learning in Python
- Deep Learning with TensorFlow
- Tensorflow Bootcamp For Data Science in Python
- Build, Train, and Deploy Your First Neural Network with TensorFlow
- Tensorflow for Beginners
- TensorFlow: Getting Started
- Understanding the Foundations of TensorFlow
- Machine Learning With TensorFlow The Practical Guide
- Tensorflow for Beginners
1. Complete Guide to TensorFlow for Deep Learning with Python
Learn how to use Google's Deep Learning Framework - TensorFlow with Python! Solve problems with cutting-edge techniques!
- Course rating: 4.2 out of 5.0 (16,536 Ratings total)
- Duration: 14 Hours
- Certificate: Certificate of completion
With this TensorFlow tutorials Coursera, you will:
- Understand how neural networks work
- Build your own neural network from scratch with Python
- Use TensorFlow for classification and regression tasks
- Use TensorFlow for image classification with convolutional neural networks
- Use TensorFlow for Time Series Analysis with recurrent neural networks
- Use TensorFlow for solving unsupervised learning problems with autoencoders
- Learn how to conduct reinforcement learning with openAI gym
- Create generative adversarial networks with TensorFlow
This TensorFlow tutorials coursera will guide you through how to use Google's TensorFlow framework to create artificial neural networks for deep learning. This course aims to give you an easy-to-understand guide to the complexities of Google's TensorFlow framework in a way that is easy to understand.
This TensorFlow tutorials coursera is designed to balance theory and practical implementation, with complete jupyter notebook guides of code and easy-to-reference slides and notes. You will also have plenty of exercises to test your new skills along the way.
2. Master Deep Learning with TensorFlow in Python
Build Deep Learning Algorithms with TensorFlow, Dive into Neural Networks, and Master the #1 Skill of the Data Scientist
- Course rating: 4.5 out of 5.0 (2,218 Ratings total)
- Duration: 6 Hours
- Certificate: Certificate of completion
With this TensorFlow tutorials coursera, you will:
- Gain a strong understanding of TensorFlow tutorials Coursera
- Build deep learning algorithms from scratch in Python using NumPy and TensorFlow
- Set yourself apart with hands-on deep and machine learning experience
- Grasp the mathematics behind deep learning algorithms
- Understand backpropagation, stochastic gradient descent, batching, momentum, and learning rate schedules
- Know the ins and outs of underfitting, overfitting, training, validation, testing, early stopping, and initialization
- Competently carry out pre-processing, standardization, normalization, and one-hot encoding
This TensorFlow tutorials coursera will start with the basics and take you to step by step toward building your very first (or second, or third etc.) Deep Learning algorithm. Moreover, it programs everything in Python and explains each line of code.
Each lecture is built upon the last practical exercises, meaning that you can practice what you’ve learned before moving on to the next step.
3. Modern Deep Learning in Python
Build with modern libraries like Tensorflow, Theano, Keras, PyTorch, CNTK, and MXNet. Train faster with GPU on AWS.
- Course rating: 4.8 out of 5.0 (2,948 Ratings total)
- Duration: 9.5 Hours
- Certificate: Certificate of completion
In this TensorFlow tutorials coursera, you will learn how to:
- Apply momentum to backpropagation to train neural networks
- Apply adaptive learning rate procedures like AdaGrad, RMSprop, and Adam to backpropagation to train neural networks
- Understand the basic building blocks of Theano
- Build a neural network in Theano
- Understand the basic building blocks of TensorFlow tutorials Coursera
- Build a neural network in TensorFlow
- Build a neural network that performs well on the MNIST dataset
- Understand the difference between full gradient descent, batch gradient descent, and stochastic gradient descent
- Understand and implement dropout regularization in Theano and TensorFlow
- Understand and implement batch normalization in Theano and Tensorflow
- Write a neural network using Keras
- Write a neural network using PyTorch
- Write a neural network using CNTK
- Write a neural network using MXNet
In this TensorFlow tutorials coursera you will learn about batch and stochastic gradient descent, two commonly used techniques that allow you to train on just a small sample of the data at each iteration, greatly speeding up training time.
You will also learn about momentum, which can be helpful for carrying you through local minima and prevent you from having to be too conservative with your learning rate. You will also learn about adaptive learning rate techniques like AdaGrad, RMSprop, and Adam which can also help speed up your training.
4. Deep Learning with TensorFlow
Channel the power of deep learning with Google's TensorFlow!
- Course rating: 4.0 out of 5.0 (237 Ratings total)
- Duration: 2 Hours
- Certificate: Certificate of completion
With this TensorFlow tutorials coursera, you will learn how to:
- Set up your computing environment and install TensorFlow tutorials Coursera
- Build simple TensorFlow graphs for everyday computations
- Apply logistic regression for classification with TensorFlow tutorials Coursera
- Design and train a multilayer neural network with TensorFlow tutorials Coursera
- Understand intuitively convolutional neural networks for image recognition
- Bootstrap a neural network from simple to more accurate models
- See how to use TensorFlow with other types of networks
- Program networks with SciKit-Flow, a high-level interface to TensorFlow tutorials Coursera
This TensorFlow tutorials coursera will offer you various complex algorithms for deep learning and various examples that use these deep neural networks. You will also learn how to train your machine to craft new features to make sense of deeper layers of data.
During the video course, you will come across topics such as logistic regression, convolutional neural networks, recurrent neural networks, training deep networks, high-level interfaces, and more.
5. Tensorflow Bootcamp For Data Science in Python
Complete Tensorflow Mastery For Machine Learning & Deep Learning in Python
- Course rating: 4.6 out of 5.0 (244 Ratings total)
- Duration: 7 Hours
- Certificate: Certificate of completion
With this course, you will be able to:
- Harness the power of anaconda/iPython for practical data science
- Learn how to install & use Tensorflow within anaconda
- Implement statistical & machine learning with Tensorflow
- Implement neural network modeling with Tensorflow
- Implement deep learning-based unsupervised learning with Tensorflow
- Implement deep learning based supervised learning with Tensorflow tutorials Coursera
This course covers all the aspects of practical data science with Tensorflow. You’ll start by absorbing the most valuable Python Tensorflow data science basics and techniques.
You will spend some time dealing with some of the theoretical concepts related to data science. However, the majority of the course will focus on implementing different techniques on real data and interpreting the results.
6. Build, Train, and Deploy Your First Neural Network with TensorFlow
In this course, you will learn the basic principles of machine learning and neural networks so you can quickly create, train, and deploy a neural network with TensorFlow.
- Course rating: 4.5 out of 5.0 ( 56 Ratings total)
- Duration: 2.8 Hours
The course includes:
- Why Learn TensorFlow?
- Setting up the TensorFlow Environment
- AI and Machine Learning Concepts
- Applying the Machine Learning Workflow with TensorFlow
- Understanding Neural Networks
- Building and Training Your First Neural Network
- Monitoring and Improving Neural Network Performance
- Deploying Your Neural Network
Here, you will learn the foundational knowledge needed to create your own neural networks.
First, you will explore the basic principles of how machine learning lets us create models that learn from data. Next, you will discover how to apply these principles to neural networks and create a model that predicts the class of clothing in an image.
Then, you will delve into how TensorFlow makes it easy to evaluate and improve the performance of neural networks with built-in tools like TensorBoard.
Finally, you will learn how to deploy your neural network and make its predictive power available to client applications.
When you are finished with this course, you will have the skills and knowledge of machine learning and TensorFlow needed to create, train, and deploy a predictive neural network.
You can take Build, Train, and Deploy Your First Neural Network with TensorFlow Certificate Course on Pluralsight.
7. Tensorflow For Beginners
A complete guide for building machine learning and deep learning solutions using Tensorflow
- Course rating: 3.9 out of 5.0 (72 Ratings total)
- Duration: 4 Hours
- Certificate: Certificate of completion
With this TensorFlow tutorials coursera, you will:
- Learn Tensorflow from the ground up
- Learn to build real-world AI and ML apps using TensorFlow
- Learn ML lifecycle and Tensorboard
- Learn to implement neural networks using Tensorflow
The TensorFlow tutorials coursera combines theory and real-world applications to offer the most practical course that can help you learn TensorFlow in a systematic manner. It will show you how you can get started on machine learning, deep learning, and building your own neural networks from scratch.
The TensorFlow tutorials coursera starts with a detailed introduction to TensorFlow and its basics, including delving into the TensorFlow Foundation. It also covers the machine learning lifecycle, TensorBoard, logical regression, neural network basics, single & multiple hidden layer neural networks, convolutional neural networks, and deep learning. In the last section of the course, you’ll use everything you’ve learned throughout the course to build an actual project from scratch.
8. TensorFlow: Getting Started
This course shows you how to install and use TensorFlow, a leading machine-learning library from Google. You'll see how TensorFlow can create a range of machine learning models, from simple linear regression to complex deep neural networks.
- Course rating: 4.0 out of 5.0 (218 Ratings total)
- Duration: 2.6 Hours
- Certificate: Certificate of completion
In this TensorFlow tutorials coursera, you will:
- See how TensorFlow tutorials Coursera easily addresses these concerns by learning TensorFlow from the bottom up.
- Be introduced to the installation process, building simple and advanced models, and utilizing additional libraries that make development even easier.
- Learn how the unique architecture in TensorFlow lets you perform your computing on systems as small as a Raspberry Pi, and as large as a data farm.
- Explore using TensorFlow with neural networks in general, and specifically with powerful deep neural networks.
9. Understanding The Foundations of TensorFlow
This course introduces TensorFlow tutorials Coursera, an open-source data flow library for numerical computations using data flow graphs.
- Course rating: 4.5 out of 5.0 (148 Ratings total)
- Duration: 2.7 Hours
- Certificate: Certificate of completion
In this TensorFlow tutorials coursera, you will:
- Learn the TensorFlow library from the very first principles
- Start with the basics of machine learning using linear regression as an example and focuses on understanding fundamental concepts in TensorFlow.
- Discover how to apply them to machine learning, the concept of a Tensor, the anatomy of a simple program, basic constructs such as constants, variables, placeholders, sessions, and the computation graph.
- Be introduced to TensorBoard, the visualization tool used to view and debug the data flow graphs.
- Work with basic math operations and image transformations to see how common computations are performed.
- Solve a real-world machine learning problem using the MNIST handwritten dataset and the k-nearest-neighbors algorithm.
10. Machine Learning With TensorFlow The Practical Guide
A comprehensive source to help you learn Machine learning with TensorFlow
- Course rating: 4.4 out of 5.0 (470 Ratings total)
- Duration: 7 Hours
- Certificate: Certificate of completion
This TensorFlow tutorials coursera includes the following topics:
- Fundamentals of Tensorflow and its installation on Windows, Mac, and Linux
- Basics of Tensorflow including tensors, operators, variables, and others
- Basics of Machine learning and its types
- Main algorithms and their implementation - Linear regression, logistic regression, KNN regression, and others
- Clustering and its approaches
- Advanced machine learning- Neural networks, convolution neural networks, recurrent neural networks
- Project on deep neural networks
This TensorFlow tutorials coursera comprises numerous topics with the sole aim to understand Tensorflow and machine learning. This course gives an insight into the basics of Tensorflow covering topics like tensors, operators, and variables. Furthermore, this course also covers advanced machine learning like neural networks, convolution neural networks, and others. Here, you’ll also gain practice by implementing it in a project on Deep Neural Networks.
11. Tensorflow for Beginners
A complete guide for building machine learning and deep learning solutions using Tensorflow
- Course rating: 4.7 out of 5.0 (622 Ratings total)
- Duration: 4 Hours
- Certificate: Certificate of completion
In this TensorFlow tutorials coursera, you will learn about:
- A detailed introduction to TensorFlow
- Familiarity with the TensorFlow foundation
- Machine learning lifecycle and TensorBoard
- Logistic regression & neural networks basics
- Single & multiple hidden-layer neural networks
- Convolutional neural networks
- Deep learning
Starting at the very beginning, this TensorFlow tutorial will focus on the basics of TensorFlow and from there progress on to difficult concepts. There are also entire sections that are dedicated to Deep Learning and also using everything you learn in this course to build a complete project from scratch.
This TensorFlow tutorials coursera combines the perfect blend of theory and practical applications to provide you with the best method of learning TensorFlow and how you can get started on machine learning, deep learning, and building your own neural networks from scratch.
Thank you for reading this. We hope our course curation would help you to pick the right course to learn TensorFlow. In case you want to explore more, you can take the free TensorFlow courses.
Hello reader! Well if you have made it to the end, then it is certain that your quest for learning is not over yet. Look no further as Coursesity presents to you a comprehensive collection of courses curated especially according to your needs.