Machine Learning And Neural Netwrok


What We Offer

We offer 2-Days AI workshop which enables participants to work on Machine Learning Applications. This course is an introduction to machine learning and algorithms. Participants will develop a basic understanding of the principles of machine learning and derive practical solutions using predictive analytics. We will also examine why algorithms play an essential role in Big Data analysis.

Outcome of ML workshop

This workshop will cover the basic algorithm that helps us to build and apply prediction functions with an emphasis on practical applications. Attendees, at the end of this workshop, will be technically competent in the basics and the fundamental concepts of Machine Learning such as:

  • Understand components of a machine learning algorithm.
  • Apply machine learning tools to build and evaluate predictors
  • How machine learning uses computer algorithms to search for patterns in data
  • How to uncover hidden themes in large collections of documents using topic modeling
  • How to prepare data, deal with missing data and create custom data analysis solutions for different industries

Machine Learning Workshop Highlights:

  • Certificate of Participation from CETA, UMT Lahore


NEURAL NEWORKS IN AI

Day

Session

Time (Hours)

Topics To Cover

First Half

I

Half an Hour

What is a neural network?

  • Basic Intution about Artificial neural network in action
  • General Structure of an artificial neural network (ANN)

II

One Hour

 

Steps involved in NN processing

  • Review of Linear and Logistic Regression Analysis
  • Cost function, Derivatives, Gradient Descent
  • Computation Graph

III

One Hour

 

Overview of Computations in NN

  • FeedForward Propagation
  • Activation functions
  • Backward propagation

IV

Half an Hour

  • Implementation of first Neural Network in Python

Second Half

1

Half an Hour

Deep L-layer Neural Network

  • Representation of Deep L-layer Network
  • Comparison with Single Layer Neural Network

II

One Hour

Implementation of Deep NN

  • Overview of Recurrent Neural Network (RNN) with Practical Example

 

III

One Hour

  • Overview of Long / Short Term Memory (LSTM) with Practical Example
  • Overview of Convolutional Neural Network (CNN) with Practical Example

IV

Half an Hour

  • Review

 

 

Feedback

 

Training Feedback to be conducted from participants

Trainers Profile

Ms. Satwat Bashir

Ms. Satwat Bashir believes in the sense of purpose with passion. Stemming her background in Computer Sciences & Cognitive Sciences, she is enthusiastic about applied approaches of Machine Learning in almost every domain. She carries a 5 years of diverse experience in Cooperate, Engineering and Research sectors and that makes her unique in understanding and applying the knowledge and skills. Her alma mater includes UET Lahore, Stanford University and Birkbeck University of London. Her world class exposure and excellence in work have been acknowledged and awarded at various international dignified platforms and forums.

Course Teacher

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