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Machine Learning Workshop

This wokshop spans 32 hours over 4 weeks.
Two times per week ,(Saturdays&Tuesdays) each session 4 hours from 8 am t​ o 12 pm.​
Starting date: 5th August 2017 
Location: iHub Studio, Ain Shams University
​CHEP Training Credit: 4 weeks
Cost: Free 
but you will pay 200 EGP as a deposit (to be returned to you when you complete the workshop till the end).

Instructor
Picture
Eng. Rana ElRobi
Registration Status
Closed
OVERVIEW
This workshop targets 3rd and 4th year students from computer science/computer Engineering,
​ It gives overview on main machine learning algorithms families and how to use each algorithm. 

GOALS
  1. Students know the main branches of Machine learning Algorithms Tree.
  2. Learn when and how to use each algorithm and its pros and cons.
  3. Practice on each algorithm even on a simple dataset to gain the experience of using the algorithms and see its results on the given data.
  4. Get familiar with using R scripts.
  5. Learn how to evaluate each algorithm result.
  6. Know where they can find data resources online.
  7. Learn how to make feature selection from the given data
​

COURSE CONTENT

Sat,5 th August
​● Introduction about Machine Learning and Data science
● Review Main basics in Linear Algebra (needed in this course)
● Linear Classifiers ( Discriminant Function Classifiers )
[Practical]
​➢ Getting started with R scripts
    ○ Load data and read it in vars
➢ Apply Least Square Classifier on given Data
➢ Apply Fisher Classifier on given Data

Tues, 8 th August
● Review on main basics in Probability (needed in this Session)
● Linear Classifiers ( Probabilistic Models
[Practical]
​➢ Apply Naive Bayes Classifier on given Data
➢ Apply Logistic Regression

Sat, 12 nd August
● Non Linear Classifiers
   ○ Knn
   ○ Weighted knn
   ○ Decision Tree
[Practical]
​➢ Apply Knn Classifier on given Data
➢ Apply weighted Knn Classifier on given Data
➢ Apply Decision Tree Classifier on given Data

Tues, 15 th August
● Clustering Techniques
   ○ K-means
   ○ K-medoid
   ○ How to choose best K
[Practical]
​ ➢ Apply K-means on given Data
➢ Apply K-medoid on given Data

Sat, 19 th August
● Clustering Techniques
   ○ Hierarchical Clustering
   ○ Specular Clustering
[Practical]
​➢ Apply Hierarchical Clustering technique on given Data
➢ Apply Specular Clustering technique on given Data

Tues, 22 nd August
​● Feature Selection
   ○ T-test Method
   ○ Forward and backward wrapper method
[Practical]
​ ➢ Apply ”T-test” method for feature selection on “ISOLTE” Dataset

Sat, 26 th August
​● Principal Component Analysis
   ○ Linear PCA
   ○ Nonlinear PCA
[Practical]
​➢ Apply ”Linear PCA” to do feature transformation
➢ Apply ”Nonlinear PCA” to do feature transformation

Tues, 29 th August
​ ● Support vector machine
   ○ Linear SVM
   ○ Nonlinear SVM
[Practical]
​ ➢ Apply ”Linear SVM” on given data.
​➢ Apply ”Nonlinear SVM” on given data.

Thurs,31 st August
​● Ensemble Learning
   ○ Bagging
   ○ Boosting
   ○ Random Forest Technique
[Practical]
​ ➢ Apply ”Bagging” , “Boosting” and ”Random forest” on
MNIST Dataset

Sat, 9 th Sep
​ ● Neural Network
   ○ Build small networks
   ○ How to build complex Network
   ○ Into to Deep Learning
   ○ Resources to Deep learning
[Practical]
​➢ Apply Neural Network on given Data.

Tues, 12 nd Sep
​● Text Mining Session (set by another Research assistant )

Copyright © Innovation Hub ( iHub )  2013

  • Home
  • General info
  • ECDC
  • CNC workshop feedback
    • PLC workshop feedback
    • Formula academy
  • Coworking Space
    • iAcademy >
      • iAcademy17
      • iAcademy_Survey >
        • iClubs >
          • iClubs 2020 Registration
      • iAcademy Personal Development Track
  • Programs
    • Entrepreneurship >
      • iSpark 2020 - Wave 1
      • Seminars >
        • Seminar Registeration Form
        • Seminars Feedback
        • Seminar Material
      • iCamp
    • iGP >
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      • Apply
    • ZEH >
      • 17zeh-submission-form
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    • iLab16
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    • EVER
  • Calendar
  • About
    • Media
  • CIB Internship
  • Front End Web Development 2021
  • NAID assistive technologies summer internship
  • iCamp Mobile Development
  • iCamp Web Development
  • NAID assistive technologies summer internship-2nd form
  • Category
  • ASU Innovates Researchers - Semi-Finals
  • Researchers'23 Interviews
  • ​​Researchers Interviews 2
  • ASU Innovates Researchers - Bootcamp