Keras Telugu

by

Guvi

Master one of the most popular libraries for artificial neural networks: Keras in python with this beginner-friendly certification course in Telugu and step out as a Keras expert into the tech industry.

₹ 1799.00

₹ 2000.00

10.05% Discount

#1

See all ranking

Keras Telugu

by

Guvi

₹ 1799.00

₹ 2000.00

10.05% Discount

#1

See all ranking

3 Modules

with Certifications

1+ Hours

of Recorded Content

4.5 Rated

by 2007 Learners

Telugu

Language

3 Modules

with Certifications

1 + Hours

of Recorded Content

4.5 Rated

by 2007Learners

Read all Reviews

Telugu

Language

About

Key Features

Content

FAQs

What's in it for You?

Learn all the core concepts of the Keras library in python and implement them practically with this expert course crafted and taught by industry experts enriching you with their job experiences. Throughout this course in Telugu, you will learn to master many concepts such as Getting Started with Colab, Fully Connected Networks, Convolutional Neural Networks, Building the Model, Training the model, NLP, Raw Data Processing, Padding, Embeddings Matrix, Fully Connected Network for Text Analysis, CNNs for Text data, RNNs for Text Data and much more. You will gain proficiency in all these concepts by implementing them first-hand in projects throughout the course which will also help you to start building your portfolio. Upon completion, you will be awarded a globally-recognized certificate to showcase the skills you have gained and impress potential employers.

Key Features:

Globally Recognised Certification

100% online and Self-paced learning

Full lifetime access to all content

Access to 4 Gamified Practise Platforms

Dedicated Forum Support to clear all your doubts

7 Days refund Policy

Topics you will learn

Beginner Module
- - Welcome to Keras for Beginners course
- - Course Walk Through
- - Getting Started with Colab 1 - First Taste of Colab
- - Getting started with Colab 2 - More about Colab
- - Getting Started with Colab 3 - Little beyond the basics of Colab
- - Introduction to Keras 1
- - Introduction to Keras 2
- - Introduction to Keras 3
- - Introduction to Keras 4
- - Introduction to Keras 5
Intermediate Module
- - Fully Connected Networks - 0 - Project Overview
- - Fully Connected Network - 1 - Preprocessing the Data
- - Fully Connected Network - 2 - Creating the Model
- - Fully Connected Network - 3 - Training the model
- - Fully Connected Network - 4 - Saving the Model
- - Fully Connected Network - 5 - Testing and Evalution
- - Fully Connected Network - 6 - Improving the Model Performance
- - OPTIONAL SUGGESTED STUDENT PROJECT 1 - Fully Connected Network
- - Convolutional Neural Networks - 0 - Project Overview
- - APPENDIX 1 - Basics of Convolutional Neural Networks
- - Convolutional Neural Network - 1 - Data Preprocessing
- - Convolutional Neural Network - 2A - Building the Model - Conv Layers
- - Convolutional Neural Network - 2B - Building the Model - Dense Layers
- - Convolutional Neural Network - 3A - Training the model
- - Convolutional Neural Network - 3B - Improving the Network Performance
- - Convolutional Neural Network - 3C - Improving the Network Performance
- - NLP - 0 - Project Overview
- - NLP - 1A - Text Data Processing - Built-in Dataset
- - NLP - 1B - Raw Data Processing
- - NLP - 1C - Raw Data Splitting
- - NLP - 2A - Tokenize Text Data
- - NLP - 2B - Padding
- - NLP - 3A - GloVe Word Embeddings
- - NLP - 3B - Embeddings Matrix
- - NLP - 4 - Fully Connected Network for Text Analysis
- - NLP - 5 - CNNs for Text data
- - NLP - 6 - RNNs for Text Data
- - NLP - 7 - LSTMs for Text Data
- - OPTIONAL STUDENT PROJECT EXERCISES NLP
Advanced Module
- - Transfer Learning - 0 - Project Overview
- - Transfer Learning - 1 - Project Overview - Introduction to Transfer Learning
- - Transter Learning - 2 - Project Overview - Introduction to Kaggle Datasets
- - Transfer Learning - 3A - Importing Kaggle Dataset
- - Transfer Learning - 3B - Data Preprocessing
- - Transfer Learning - 4 - Base Model
- - Transfer Learning - 5 - Keras Functional API
- - Transfer Learning - 6 - Classification Layers
- - Transfer Learning - 7 - Training with fit_generator
- - Course Wrapup - Beyond The Basics

Course Offerings

Certificate you will get

IITM Pravartak certified Python certification.

Certificates are globally recognized & they upgrade your programming profile.

Certificates are generated after the completion of course.

After this Course

Install and configure Keras on your local machine with ease.

Train a model Keras model with Colab and run it on any browser.

Implement a fully connected neural network.

Develop a deep learning network from scratch with Keras in python as part of a Capstone Project.

Have a solid understanding of Convolutional and Recurrent ANNs.

Adopt Deep Learning, NLP, and convolutional networks in a simple yet accurate way.

Pre Requsites

Basic knowledge of Deep Learning and the Python programming language.

The will to build and train deep learning models with Keras in python.

Course is for

Freshers

Professionals

Students

FAQ's

What is a Keras course in Telugu?

A Keras course in Telugu teaches individuals how to use the Keras library, a popular open-source deep learning framework. Keras simplifies the process of building and training artificial neural networks by providing a user-friendly interface for developing complex models. These courses typically cover the basics of machine learning, deep learning, and the various components of the Keras library, such as layers, activation functions, and loss functions as well as teach you how to master them.
What is Keras in python?

Keras is a popular open-source neural network library in Python that provides a high-level interface for building and training deep learning models. It is built on top of lower-level libraries such as TensorFlow, CNTK, and Theano, and allows for rapid prototyping and experimentation with neural network architectures. Keras in python is known for its ease of use, modularity, and support for a wide range of neural network types, including convolutional networks, recurrent networks, and more.
Why learn Keras course in Telugu online?

Learning Keras in python course in Telugu online can offer numerous benefits. Keras is a popular deep-learning framework that enables developers to create and deploy machine-learning models efficiently. Taking an online course in Keras in Telugu can help individuals to gain a comprehensive understanding of the framework, its functions, and its applications with ease and the added comfort of self-paced learning. You will also gain industry tips and tricks from top mentors and build real-world projects as part of your portfolio. This can lead to exciting job opportunities in the field of AI and data science. Hence, an online course such as this one by GUVI will help you to a great extent.
What are the benefits of learning Keras in Telugu?

Learning Keras in Telugu helps us simplify the process of building and testing neural networks, allowing for faster experimentation with different architectures, and providing access to pre-trained models and resources. Keras also offers an intuitive and user-friendly API, making it a great tool for beginners and experienced developers alike. No wonder it is a must-have skill for major tech roles in the industry.
Is Keras hard to learn?

Keras, a popular deep-learning library, is relatively easy to learn due to its user-friendly API and extensive documentation. The library provides high-level abstractions, making it easy for beginners to develop and train neural networks quickly. While some experience in Python and machine learning concepts is useful, Keras is designed to be accessible to people with different levels of expertise. With an excellent learning resource such as this course by GUVI and practice, anyone can master Keras efficiently.