Machine Learning and Python

Trainer: Vlad Iliescu, Senior Architect

Upcoming date: 30th of November, 2018 from 13:00 - 17:00

Location: Iasi

Price: 100€/attendee (+ VAT)

Max. attendees: 10

AI is the new electricity” says Andrew Ng, one of the pioneers of AI and online learning. His remark may be an overstatement, bit there’s no denying the impact AI has had, is having, and will continue to have on our lives, at both personal and professional levels.

One of the core instruments of AI is Machine Learning, and by attending this workshop you will get the chance to learn about ML and understand how you can use it effectively.

During this workshop, you will learn about the types of problems solved by Machine Learning, the most used algorithms, and the metrics used to compare their performance.

After attending this workshop, you will be able to assess a Machine Learning problem, decide how to approach it using ML, and train and evaluate a predictive model.

Workshop Agenda

  1. Introduction to Machine Learning
    a. What is Machine Learning and how it relates to Artificial Intelligence
    b. The types of Machine Learning and the problems they’re designed to solve
    c. Metrics used for each of the Machine Learning types
    d. Most common Machine Learning algorithms, how they work, what datasets they’re best used for
  2. Machine Learning using Python
    a. Working with data in Python using pandas
    b. Visualizing data with matplotlib and seaborn
    c. Using Jupyter notebooks for data science
    d. Making use of the algorithm implementations in scikit-learn
    e. Training models and evaluating them
  3. Machine Learning using Python
    a. Compete with the other attendees in analysing an unknown dataset and using it to train a predictive model
    b. Once all models are trained, we will score their performance over an unknown test dataset, and reveal the best-performing model

Students Prerequisites

  1. Every student will have his/her own laptop. For best results, it is not advisable to multiple people working on the same machine
  2. An IDE/code editor of choice (Sublime Text, Atom, Visual Studio Code, WebStorm, etc.)
  3. A local Anaconda installation
  4. A desire to learn

Thank you for reading. Now help us spread the ❤️ by sharing.