Learn complete Machine Learning , Deep Learning and Neural Networks in Tensorflow

Learn the basics of Machine Learning

Understand how Machine Learning Model Works

Learn How To Train Machine Learning Models

Learn About Deep Learning,Convolutional neural network

Python Basic knowledge required

TensorFlow Tutorial for Bners: Your Gateway to Building Machine Learning Models

It is evident from a Market Research Future Indeed report, which reveals that the machine learning jobs market is projected to be worth almost $31 billion by 2024. Machine learning creates algorithms that enable machines to learn and apply intelligence without being directed, and TensorFlow is an open-source library used for building machine learning models.

In this TensorFlow tutorial, we are going to cover the following topics:

What is deep learning

Top libraries to develop deep learning applications

What is TensorFlow

Why use TensorFlow

Building a computational graph

Programming elements in TensorFlow

Introducing Recurrent Neural Networks (RNN)

Use case implementation of RNN using TensorFlow

What is Deep Learning

Deep learning is a subset of machine learning. There are certain specialties in which we perform machine learning, and that's why it is called deep learning. For example, deep learning uses neural networks, which are like a simulation of the human brain. Deep learning also involves analyzing large amounts of unstructured data, unlike traditional machine learning, which typically uses structured data. This unstructured data could be fed in the form of images, video, audio, text, etc.

The term 'deep' comes from the fact that a neural network can have multiple hidden layers.

Programmers who want to master deep learning and neural networks






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