Certified Keras Professional

How It Works

  1. 1. Select Certification & Register
  2. 2. Receive a.) Online e Learning Access (LMS)    b.) Hard copy - study material
  3. 3. Take exam at chosen Date and Venue
  4. 4. Get certified & Increase Employability

Test Details

  • Duration: 60 minutes
  • No. of questions: 50
  • Maximum marks: 50, Passing marks: 25 (50%).
  • There is NO negative marking in this module.
  • 70 exam centres in India.

Benefits of Certification

Deliverables

e-learningHard CopyPractice Test
Rs.3,499 /-

Keras is an open-source neural-network library written in Python. It is capable of running on top of TensorFlow, Microsoft Cognitive Toolkit, Theano, or PlaidML. Designed to enable fast experimentation with deep neural networks, it focuses on being user-friendly, modular, and extensible.

Why should one take Keras Professional Certification?

This Course is intended for professionals and graduates wanting to excel in their chosen areas. It is also well suited for those who are already working and would like to take certification for further career progression.

Earning Vskills Keras Professional Certification can help candidate differentiate in today's competitive job market, broaden their employment opportunities by displaying their advanced skills, and result in higher earning potential.

Who will benefit from taking Keras Professional Certification?

Job seekers looking to find employment in data science or analysis departments of various companies, students generally wanting to improve their skill set and make their CV stronger and existing employees looking for a better role can prove their employers the value of their skills through this certification. 


Apply for Keras Professional Certification

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TABLE OF CONTENT




Keras Basics

  • You have just found Keras.
  • Multi-backend Keras and tf.keras
  • Guiding principles
  • Installation
  • Configuring Keras backend

Using Keras

  • Sequential model
  • Functional API

Models

  • About Keras models
  • Sequential
  • Model (functional API)

Layers

  • About Keras layers
  • Core Layers
  • Convolutional Layers
  • Pooling Layers
  • Locally-connected Layers
  • Recurrent Layers
  • Embedding Layers
  • Merge Layers
  • Advanced Activations Layers
  • Normalization Layers
  • Noise layers
  • Layer wrappers
  • Writing your own Keras layers

Preprocessing

  • Sequence Preprocessing
  • Text Preprocessing
  • Image Preprocessing
  • Losses
  • Metrics
  • Optimizers
  • Activations
  • Callbacks
  • Datasets
  • Applications
  • Backend
  • Initializers
  • Regularizers
  • Constraints
  • Visualization
  • Scikit-learn API
  • Utils

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