26
oct
2017

Intro to Machine Learning

Organizers

  • Unde: Bucharest, Romania
  • Când: 26 octombrie 2017, ora 09:00
  • Info: 2 day course - October 26-27
Conferinta Agora

Intro to Machine Learning – By Mr. Dani Livne

 

Course Overview:

Machine Learning use a set of algorithms which enables computers to solve problems that are classified on a higher complexity level than traditional algorithms. Examples of such cases are: to predict a consumer behavior by its past choices, recognize a person within an image, “understand” written text, to predict   a system failure or a cyber-attack.

Machine learning algorithms allow the computer to train and learn from its own mistakes and thus perfect its performance on new data.

This course gives the basis of understanding the data scientist environment, focusing mainly on common frameworks in order to enable selecting the appropriate approach to the problems at hands.

We will review various use cases and implement appropriate models and tools.

Who should attend?

Managers and architects who like to understand the different problems that are suitable for machine learning and exercise different frameworks.

Prerequisites:

Basic programming skills in C, Java or any other language. Basic knowledge in probability and statistics.

Lecturer: Dani Livne

Mr. Dani Livne is a lecturer on topics of algorithms and data science at Logtel.

Dani holds an MBA and Mathematics MCs. degrees from Tel-Aviv university and has over 20 years of research and development in various high tech companies.

Course Content:

Day 1:

1. Introduction to Machine Learning

  • Examples and use cases
  • Statistics 101
  • Machine learning workflow

2. Data preparation using various tools

  • Exploratory data analysis
  • Cleaning the data
  • Filtering and scaling
  • Outliers and null values

PCA

3. Selecting machine learning algorithms

  • Regression and decision trees
  • Statistical reasoning

Clustering

4. Weka Introduction

  • Using the Explorer

Different use cases

 

Day 2:

5. Machine learning in the cloud, Big Data

  • Classification
  • Association Rules
  • Decision Trees

6. Validation of Results

  • Standard metrics
  • Precision and Recall
  • ROC curve analysis

7. Weka for Developers

  • Using the Experimenter
  • Running different models
  • Adding new algorithms

8. Summary

 

Cost:

 

until September 15th: 3200 RON per participant (VAT included)

from September 16th until September 29th: 3600 RON per participant (VAT included)

from September 30th: 4500 RON per participant (VAT included)

For groups larger than 10 participants we offer a 10% discount.

 

For invoicing and other information please contact us at conferinte@agora.ro