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Introduction to Tensorflow and Keras

Learn tensorflow & keras in this free online training. Tensorflow & keras course is taught hands-on by experts. Learn how to get started with tensorflow and convolution process in details. Best for beginners. Enroll for free now!

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Introduction to Tensorflow and Keras

5.25 Learning Hours . Beginner

Skills you’ll Learn

About this course

This Introduction to TensorFlow and Keras course will enrich your knowledge about all the essential Python libraries and guide you to install them step by step. It will start by explaining what TensorFlow is and its various functionalities. It will then take you to get a brief understanding of the prerequisites to understand tensors before moving on to the installation chapter. Once your concept of TensorFlow is clear, the course will have you navigate through Neural Networks and discuss how you can write Tensor code to perform distinct operations. Before wrapping up the course, you will also learn about the newer version (TensorFlow 2.x) and learn to perform Linear Regression using TensorFlow. In the last phase, the course will take you through the hands-on session, which will discuss two use cases and finally throw light on what Keras is, its features, character recognition, and image classification using CNN.

 

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Course Outline

Introduction for tensorflow

With the high demand for Deep Learning, it is essential to learn about TensorFlow to create Deep Learning models. Here, we will learn what TensorFlow is, the essential library, and the in-demand skill. 
 

Brief About TensorFlow-2

This section will continue discussing the various functionalities of TensorFlow, including Google Colab, reasons to learn TensorFlow, and Languages & OS supported by TensorFlow.
 

What are Tensors?

This section will discuss the prerequisites to understand tensors, including Linear Algebra, Vector Calculus, and Python Calculus, and how they work together to provide effective results.

 

 

 

How to install TensorFlow?

In this section, you will learn about the latest version and compatibility and how you can install TensorFlow based on what GUI/CLI you use for Python.

 

Introduction to neural networks

You will understand what Neural Networks are and how they are a pathway to Artificial Intelligence using Deep Learning. This section will also give a brief idea of weights & mathematics in Neural Networks.
 

Getting Started with TensorFlow

In this section, you will understand what a Tensor looks like, how it works, how we can programmatically write the Tensor, and how to get it to perform operations for us eventually.

 

 

Basic Demo on TensorFlow-2

You will learn about the new version- of TensorFlow 2.x, its features, and what's new in this version.
 

Linear Regression Using TensorFlow-2

This section will throw light on how to perform Linear Regression using TensorFlow using different linear equations with step-by-step explanations.
 

Demo #1: MNIST Character Recognition with TensorFlow

This will be a hands-on session discussing 2 use cases: Digit classification using the MNIST dataset & image classification using CNN. This chapter will talk about the former demo.

 

Demo #2: Binary classifier using Convolutional Neural Network

In this section, you will get clarity on what CCN is and then go on to solve the demo use case.

 

Getting Started with Keras-2

Learn about the various features of Keras, Keras Vs. tf.keras, and then we will look at the code snippets to have a better understanding.
 

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Ratings & Reviews of this Course

Reviewer Profile

5.0

Learning Outcomes from This Course Were Very Helpful
I really enjoyed this course as it really helped me with new learning of TensorFlow and Keras to kickstart my journey in artificial intelligence.
Reviewer Profile

5.0

I Found the Course Content to Be Well-Structured and Easy to Follow
I particularly appreciated the way the course content was broken down into manageable modules. Each module built upon the previous one, making it easy to follow the progression of the material.
Reviewer Profile

5.0

Videos Are Easy to Understand and Very Useful to Cover Extra Topics
The 'Introduction to TensorFlow and Keras' course provided a clear and practical foundation to get started with deep learning. The explanations are easy to follow, and the hands-on examples made complex concepts like neural networks, tensors, and model building much more accessible.
Reviewer Profile

5.0

Very Informative and Interesting Topic, Well Explained and Presented
It was easy to follow the course. I really enjoyed the in-depth practical demos and felt it was easy to follow along and try it out for myself!

Earn a certificate of completion

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Get free course content

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Learn at your own pace

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Master in-demand skills & tools

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Introduction to Tensorflow and Keras

5.25 Learning Hours . Beginner

Frequently Asked Questions

What are the prerequisites required to learn this Introduction to TensorFlow & Keras Course?

Learning TensorFlow and Keras requires no prerequisites. But it's preferred that learners have a fundamental understanding of statistics, algebra, and Machine Learning.

 

How long does completing this free Introduction to TensorFlow & Keras Course take?

This course contains approximately 3 and a half hours of video content you can watch and learn in your comfort.

 

Will I have lifetime access to the free course?

Yes, you will get lifetime access to this free Introduction to TensorFlow and Keras course that you can view anytime.

 

What are my next learning options after this Introduction to TensorFlow and Keras course?

Once you have completed this Introduction to TensorFlow and Keras Course, you can go ahead and learn about Neural Networks, Keras, Deep Learning Models, and work on various Machine Learning projects. You can also enroll in the AI and Machine Learning course to pursue a promising career. 

 

Is it worth learning TensorFlow and Keras?

The majority of AI and ML professionals and data scientists worldwide use Tensorflow, one of the top frameworks in the world. It makes your Machine Learning and Deep Learning coding simple, it is easy to use, comes with extensive documentation, and accepts Keras as a high-level API, making it a two-framework solution. So, yes, it is worth learning.

 

What are TensorFlow and Keras used for?

Google created the open-source library TensorFlow specifically for Deep Learning apps. TensorFlow was created without Deep Learning in mind to handle huge mathematical calculations. Whereas deep models can be produced using Keras and then deployed on mobile devices.

 

Why are TensorFlow and Keras so popular?

TensorFlow simplifies Machine Learning to another level, and it makes it simple for anyone to create ML models with pre-trained models, data, and high-level APIs. Researchers and students extensively use TensorFlow to develop models and conduct research. 

 

Best practices for lowering the cognitive load are employed by Keras, which provides consistent and easy APIs, reduces the number of user steps necessary for typical use cases, and offers clear and concrete feedback in the event of user error. Because of this, Keras is simple to use and learn & eventually gained popularity.

 

What jobs demand that you learn TensorFlow and Keras?

There are many job profiles you can land after you earn competency in TensorFlow and Keras, some of which are:

  • Machine Learning Engineer
  • Machine Learning Scientist
  • Data Scientist
  • Python Developer
  • Software Developer

 

What knowledge and skills will I gain upon completing this Introduction to TensorFlow & Keras Course?

You will learn what TensorFlow, Keras, and CNN are, their features, how they work, how you can install them, how they are used to create Deep Learning models, and also gain an extensive understanding of Neural Networks.

 

How much does this Introduction to TensorFlow and Keras Course cost?

Great Learning Academy is offering the course for free in its entirety. This course is a great place to start for anyone looking to learn more about TensorFlow, Keras, and CNN to launch a career in AI and ML.

 

Is there a limit on how many times I can take this Introduction to TensorFlow & Keras Course?

There isn't any such limit on how many times you can view the course. You are welcome to return and review the course again whenever you need to.

 

Can I sign up for multiple courses from Great Learning Academy at the same time?

You can enroll in as many courses from Great Learning Academy as you like and pursue several courses at once.

 

Why choose Great Learning Academy for this Introduction to TensorFlow & Keras Course?

Great Learning, a popular ed-tech firm, believes in transforming lives. Popular free online courses are offered by the Great Learning Academy initiative to help learners excel in the fields they are interested in free of cost.

 

Great Learning, a popular ed-tech firm, believes in transforming lives. Popular free online courses are offered by the Great Learning Academy initiative to help learners excel in the fields they are interested in free of cost.

 

 

Who is eligible to take this Introduction to TensorFlow & Keras Course?

No eligibility criteria are set for this course. You can further your learning in TensorFlow, Keras, CNN, and Neural Networks, by directly enrolling in the course.

 

What are the steps to enroll in this course?

To enroll in the Introduction to TensorFlow & Keras Course, follow the steps mentioned below: 

1. Once you are on the "Introduction to TensorFlow & Keras" course page, locate the "ENROL FOR FREE" option at the top right of the page and click on it.

2. You will be taken to the signup page. enter your details and create your account.

3. You will be navigated to the course content after your profile is verified.

4. Start viewing the videos and your learning journey.

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Other Artificial Intelligence tutorials for you

Understanding Tensorflow and Keras

 

TensorFlow and Keras are powerful open-source tools for creating machine-learning models. TensorFlow is a library for numerical computation and deep learning. At the same time, Keras is a high-level neural network API. Together; they provide a comprehensive set of tools for developers to create modern artificial intelligence (AI) applications.

 

Introduction to TensorFlow

 

TensorFlow is an open-source software library for numerical computation and deep learning. It was developed by Google and is widely used for machine learning, data science, and artificial intelligence. It provides extensive tools to help developers create and deploy machine learning models. It supports both CPU and GPU hardware, and it can be used in a variety of languages, including Python, Java, and C++.

 

Brief About TensorFlow-2

 

TensorFlow 2 is the latest version of the library, released in 2019. It offers many new features and improvements over the previous version, such as a more intuitive API, eager execution, improved performance, and support for custom training loops. TensorFlow 2 also makes it easier to use advanced techniques such as transfer learning and generative adversarial networks.

 

What are Tensors?

 

Tensors are multi-dimensional arrays of data. They are the fundamental building blocks of TensorFlow. Tensors are used to represent and manipulate data in machine-learning models. The data can be numerical (floating-point values) or categorical (text, images, etc.).

 

How to Install TensorFlow?

 

TensorFlow can be installed on various platforms, including Windows, Linux, and MacOS. It can be installed using the official TensorFlow package or through Anaconda. We recommend using the Anaconda distribution, as it provides a convenient way to manage multiple versions of Python and TensorFlow.

 

Introduction to Neural Networks

 

Neural networks are a machine learning model inspired by the structure and function of the human brain. They are used to solve complex problems, such as image and voice recognition, natural language processing, and machine translation. Neural networks consist of layers of interconnected neurons that process data and make predictions.

 

Basic Demo on TensorFlow-2

 

To get started with TensorFlow 2, we recommend going through the official tutorials. These provide step-by-step instructions on how to use the library to create machine-learning models. There are also many example programs available to help you understand the basics of TensorFlow.

 

Getting Started with Keras-2

 

Keras-2 is a high-level neural network API built on top of TensorFlow. It makes it easier to create and deploy machine learning models. With Keras, you can create neural networks with just a few lines of code. It also provides a wide range of tools to help you optimize your models and make them more accurate.

 

Free Course on TensorFlow and Keras

 

If you want to learn more about TensorFlow and Keras, we recommend taking the free course on “TensorFlow and Keras” from Udemy. In this course, you will learn about machine learning and deep learning fundamentals and how to use TensorFlow and Keras to create powerful AI applications. At the end of the course, you will receive a certificate of completion.

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