Objectives:

       Provide a larger picture of Machine Learning (problems, techniques, challenges etc.) to beginner and/or moderate level of audience interested to explore about Machine Learning.

       To acquaint the audience with the different libraries, tools and frameworks for implementing Machine Learning

        Give a hands-on experience about machine learning based on real world examples ( Dataset preparation, Developing a model, Training and Testing the model, Evaluating the model)

Resource persons:

         Dr. Bal Krishna Bal, Associate Professor, Information and Language Processing Research Lab, Department of Computer Science and Engineering. 

        Mr. Santosh Regmi, Co-founder and CEO, KEIV Technologies, Assistance Professor Gandaki College of Engineering and Science. 

">

Training Description

Objectives:

       Provide a larger picture of Machine Learning (problems, techniques, challenges etc.) to beginner and/or moderate level of audience interested to explore about Machine Learning.

       To acquaint the audience with the different libraries, tools and frameworks for implementing Machine Learning

        Give a hands-on experience about machine learning based on real world examples ( Dataset preparation, Developing a model, Training and Testing the model, Evaluating the model)

Resource persons:

         Dr. Bal Krishna Bal, Associate Professor, Information and Language Processing Research Lab, Department of Computer Science and Engineering. 

        Mr. Santosh Regmi, Co-founder and CEO, KEIV Technologies, Assistance Professor Gandaki College of Engineering and Science. 

Training Syallabus

July 1, 2018 ( 9:30 AM to 12:30 PM ) 

               Introduction to Machine Learning

                Fundamentals of Machine Learning

o   Machine Learning Perspective of Data

o   Feature Engineering

o   Machine Learning Problems

§  Classification

§  Regression

§  Clustering

o   Machine Learning Approaches

§  Supervised

§  Semi-supervised

§  Unsupervised

          Evaluating and fine-tuning machine learning models


        July 1, 2018 ( 1:00 PM to 3:30 PM ) 

               -  Overview of tools and libraries

               -  Walk through of live demos and examples

                 - Dataset preparation for Day 2 hands-on 


       July 2, 2018 ( 9:30 AM to 12:30 PM )

                    -   Recurrent Neural Network

             -  Deep and Natural Language Processing

        - Reinforcement Learning


July 2, 2018 (1:00 PM to 3:30 PM )

Hands-on tutorials

o   Text classification

o   Sentiment Analysis

Topic Modeling

Training Fee

Payment of registration fees: Please deposit a sum of NRs. 2500 in the following bank account and upload the deposit slip here: 
       Account name: Kathmandu University   
       Account Number: 00501030250009 
       Bank name:  Nepal Investment Bank 
       Branch: Banepa

Deadline for this vacancy has been expired.