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IIPM Certified Training on Deep Learning Algorithms & Applications

IIPM Certified Training on Deep Learning Algorithms & Applications

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IIPM Certified Training on Deep Learning Algorithms & Applications

2021-05-24 15:30 to 2021-05-28 17:00
May 24, 2021

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Pantech eLearning

8925533488

training@pantechelearning.com

https://www.pantechelearning.com/

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IIPM Certified Training on Deep Learning Algorithms & Applications

2021-05-24 15:30 to 2021-05-28 17:00
May 24, 2021

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About the Program

This course is designed to provide an exposure to the fundamentals of Artificial Intelligence and Deep Learning. Participants will learn to apply deep learning techniques to solve the real-world research and industry problems. Hands-on training and practice sessions will help participants gain confidence on deep learning concepts by creating their own neural networks, object detection models etc. The course will be useful for faculty of engineering and sciences who are interested in the learning recent AI trends and their applications in areas like image processing, computer vision and robotics.

 

Technologies and Tools Covered

  • Python IDE
  • Anaconda Navigator
  • Jupyter Notebook
  • Keras
  • Darknet

 

LEARNING PATH

Importance of the Course

  • Artificial intelligence and Deep learning have long since found their way into large parts of industry. Success has most recently been achieved in autonomous driving, medical image processing or material testing. In future, Artificial Intelligence (AI) will play an even greater role in numerous industries and scenarios. To remain fit for this future, companies have to deal with the basics of AI and machine learning.
  • These basics are imparted in the workshop on Deep Learning, which bundles the sheer flood of information and offers you a compact overview of theory and practice in Deep learning. You receive the hands-on knowledge you need to integrate the enormous potential of artificial intelligence into your product portfolio and value chain.
  • This workshop is very practice-oriented. Half of it consists of applied exercises on a consistent topic. You will learn the relevant methods and practices around Deep learning while focusing on artificial neural networks, the basis for Machine learning.

 

  1. Introduction to Python and Machine Learning

 

SESSION

CLASS TOPICS

1 Introduction to Python Programming
2 Software Installation IDE, Anaconda Navigator
3 Introduction to Machine Learning and Deep Learning Package
4 Training Machine Learning Model
5 Inference from Machine Learning Model

 

  1. Keras Fundamentals for Deep Learning

Here’s how to make a Sequential Model and a few commonly used layers in deep learning.

Example of how to make convolutional layer as the input layer with the input with filters of size and use ReLU as an activation function. How to down sample the input representation, use MaxPool2d and specify the kernel size. Adding a Fully Connected Layer with just specifying the output Size. Adding dropout layer with Compiling, Training, and Evaluate

 

SESSION

CLASS TOPICS

1 Installing Procedure of KERAS
2 Loading a Data
3 Define a Neural network in keras
4 Compile a Keras model using the efficient numerical backend.
5 Train a model on data.
6 Evaluate a model on data and make predictions with the model.

 

 

CNN and Project Working

 

SESSION

 

CLASS TOPICS

 
1 Building a CNN model
 
2   CNN for image classification
 
3   Introduction to LSTM, GRU
 
4   Applications in machine translation language modelling and sentiment classification.
 

 

Projects & Assignments

Practical 1 : Using CSV Dataset.

Practical 2 : Using Image Classification.

Practical 3 : Building an AI application for sentiment classification

Practical 4 : AI Face Recognition using Deep Learning .

 

Training Methodology

The Program is mix of Theory sessions, Quizzes, Hands on Sessions, Interaction with Experts, Assignments and Practical Exercises. Maximum Impetus is given to Hands on Sessions so as to enable the participants with the maximum knowledge transfer and satisfaction. The ratio of the theory, practical sessions will be 30:70.

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Mahima NP
1 month ago

It was very informative session and enjoyed the session. Thank you so much for opportunities.

College / Organization Name
Sri Venkateswara College of engineering
Dr.Sunitha
1 month ago

Satisfactory

College / Organization Name
RRIT
Palagati Anusha
1 month ago

Good sessions need more sessions

College / Organization Name
KMMITS, Tirupati
V Harsha Shastri
1 month ago

Very good sessions

College / Organization Name
Loyola Academy
Satya Prakash
1 month ago

The content covered in a span of 5 days was great, clearly explained.

College / Organization Name
ZCOER
Muhannad A
1 month ago

The all sessions was great 👍

Rama Kishore Reddy Somala

Satisfactory

College / Organization Name
CMR Engineering College
Dr Minakshi Pradeep Atre
Dr Minakshi Pradeep Atre
1 month ago

The session on Deep Learning was engaging and learnt many new things. Thanks to the trainer!

Pooja Chavan
1 month ago

Very informative

College / Organization Name
Lords Institute Of Engineering & Technology
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