What is TensorFlow?
Tensorflow is the world’s most popular library for deep learning, and it’s built by Google. It is the library of choice for many companies doing AI and machine learning.
In other words, if you want to do deep learning, you gotta know Tensorflow.
It is an end-to-end open source machine learning platform for everyone. It is one of the most popular open-source Deep Learning Library. It is designed to do both numeric and neural network-oriented problems.
TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications.
- It is easily trainable on CPU as well as GPU for distributed computing.
- It has a huge Support team as it is developed by Google.
- Easy Access to Statistical Distributions such as Bernoulli, Beta, Chi2, Uniform, and Gamma.
- There are number of courses / certifications available to self-start your career in Deep Learning with TensorFlow. These courses are given in online or offline. The main trouble students face is to choose the best out of these courses.
How to choose the right online course for you?
Choosing the right course is always a difficult task for any individual.
So I have selected all these Courses based on some basic Criteria:
- Course Content/Description
- Course Quality,
- Knowledgeable and Professional Trainers
- Career Opportunities,
- Highest Reviewed,
- Best Sellers,
- Highest Rated,
- Newest etc
For most of these Courses you will Get :
1.) Full lifetime access
2.) Access on mobile and TV
3.) Certificate of Completion
4.) 30-Day Money-Back Guarantee
- You will get a Shareable Certificate and Course Completion Certificates once done.
- Also, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.
Who Should Enroll?
- Who is a starter/beginner who is interested to learn Tensorflow and have basic knowledge of Machine Learning algorithms.
With the introduction of few newly introduced courses, it has turned out to be considerably more hard to make a right decision. The dread of putting in unworthy courses keeps to remain the greatest obstacle for students.
Below are the list of Top 10 Best Tensorflow Courses Courses available as of now!
TOP 10 Best Tensorflow Courses Online In 2021
ENROLL Course FREE http://bit.ly/2lMfpZe
What You Learn:
- Understanding Tensors &Installing Tensorflow 2
- Discovering the Basics of Tensorflow and Basic Computations
- Implementing Gradient Descent with Autodiff
- Developing a Model Structure
- Creating Custom Modules and Importing Datasets
- Build, Train, and Evaluate ANN Model
- Visualizing and Saving Models
ENROLL For FREE https://bit.ly/3lzGhVG
TensorFlow is an end-to-end open-source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML, and developers easily build and deploy ML-powered applications. TensorFlow is commonly used for machine learning applications
DeepLearning.AI TensorFlow Developer Professional Certificate
ENROLL For FREE https://bit.ly/33H5PZZ
TensorFlow is one of the most in-demand and popular open-source deep learning frameworks available today. The DeepLearning.AI TensorFlow Developer Professional Certificate program teaches you applied machine learning skills with TensorFlow so you can build and train powerful models.
Machine Learning with TensorFlow on Google Cloud Platform Specialization
ENROLL For FREE http://bit.ly/2INSAho
What is machine learning, and what kinds of problems can it solve? What are the five phases of converting a candidate use case to be driven by machine learning, and why is it important that the phases not be skipped? Why are neural networks so popular now? How can you set up a supervised learning problem and find a good, generalizable solution using gradient descent and a thoughtful way of creating datasets? Learn how to write distributed machine learning models that scale in Tensorflow, scale out the training of those models. and offer high-performance predictions.
Advanced Machine Learning with TensorFlow on Google Cloud Platform Specialization
ENROLL For FREE http://bit.ly/2QqFnxe
This 5-course specialization focuses on advanced machine learning topics using Google Cloud Platform where you will get hands-on experience optimizing, deploying, and scaling production ML models of various types in hands-on labs. This specialization picks up where “Machine Learning on GCP” left off and teaches you how to build scalable, accurate, and production-ready models for structured data, image data, time-series, and natural language text. It ends with a course on building recommendation systems.
TensorFlow 2 for Deep Learning Specialization
ENROLL For FREE https://bit.ly/2RCrdKm
This Specialization is intended for machine learning researchers and practitioners who are seeking to develop practical skills in the popular deep learning framework TensorFlow.
The first course of this Specialization will guide you through the fundamental concepts required to successfully build, train, evaluate and make predictions from deep learning models, validating your models and including regularisation, implementing callbacks, and saving and loading models.
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
ENROLL For FREE http://bit.ly/2lMfpZe
The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new deeplearning.ai TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization.
Natural Language Processing in TensorFlow
ENROLL For FREE http://bit.ly/2k9pFud
This Specialization will teach you best practices for using TensorFlow, a popular open-source framework for machine learning.
In Course 3 of the deeplearning.ai TensorFlow Specialization, you will build natural language processing systems using TensorFlow. You will learn to process text, including tokenizing and representing sentences as vectors, so that they can be input to a neural network. You’ll also learn to apply RNNs, GRUs, and LSTMs in TensorFlow. Finally, you’ll get to train an LSTM on existing text to create original poetry!
TensorFlow: Data and Deployment Specialization
ENROLL For FREE http://bit.ly/2VPWuNa
In this four-course Specialization, you’ll learn how to get your machine learning models into the hands of real people on all kinds of devices. Start by understanding how to train and run machine learning models in browsers and in mobile applications.
Learn how to leverage built-in datasets with just a few lines of code, learn about data pipelines with TensorFlow data services, use APIs to control data splitting, process all types of unstructured data, and retrain deployed models with user data while maintaining data privacy. Apply your knowledge in various deployment scenarios and get introduced to TensorFlow Serving, TensorFlow, Hub, TensorBoard, and more.
Tensorflow 2.0: Deep Learning and Artificial Intelligence
ENROLL For FREE http://bit.ly/3qcnYsG
This course is for beginner-level students all the way up to expert-level students. How can this be?
If you’ve just taken my free Numpy prerequisite, then you know everything you need to jump right in. We will start with some very basic machine learning models and advance to state of the art concepts.
Along the way, you will learn about all of the major deep learning architectures, such as Deep Neural Networks, Convolutional Neural Networks (image processing), and Recurrent Neural Networks (sequence data).
Complete Guide to TensorFlow for Deep Learning with Python
ENROLL For FREE http://bit.ly/3a9dTHF
This course 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. Other courses and tutorials have tended to stay away from pure tensorflow and instead use abstractions that give the user less control. Here we present a course that finally serves as a complete guide to using the TensorFlow framework as intended, while showing you the latest techniques available in deep learning!
Complete Tensorflow 2 and Keras Deep Learning Bootcamp
ENROLL For FREE http://bit.ly/3jCgYCU
This course will guide you through how to use Google’s latest TensorFlow 2 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 2 framework in a way that is easy to understand.
We’ll focus on understanding the latest updates to TensorFlow and leveraging the Keras API (TensorFlow 2.0’s official API) to quickly and easily build models. In this course we will build models to forecast future price homes, classify medical images, predict future sales data, generate complete new text artificially and much more!
Browser-based Models with TensorFlow.js
ENROLL For FREE https://bit.ly/37X8GA6
Bringing a machine learning model into the real world involves a lot more than just modeling. This Specialization will teach you how to navigate various deployment scenarios and use data more effectively to train your model.
In this first course, you’ll train and run machine learning models in any browser using TensorFlow.js. You’ll learn techniques for handling data in the browser, and at the end you’ll build a computer vision project that recognizes and classifies objects from a webcam.