Introduction to machine learning

Machine learning training

Prerequisites

Python syntax

Skills your team will gain

Selected machine learning and deep learning concepts and algorithms.

The ability to create machine learning and deep learning algorithms in Python using its libraries.

The ability to create pipelines for solving real‑life problems.

Tools and metrics for evaluating machine learning models.

Guidance on how to manage data science projects and how they differ from software development ones.

Duration

3 days

Agenda

Part 1

Machine learning basics

  • Data science ideas
  • The programming environment: Python or R and its data science libraries, Jupyter Notebook
  • Data exploration and preprocessing

Part 2

Machine learning techniques

  • Feature engineering
  • Linear regression, logistic regression
  • Reducing dimensionality

Part 3

Random forests, managing the data science process

  • Random forest, XGBoost, !!LightGBM
  • Organizing teamwork
  • Managing and tracking experiments

Contact us

Locations
  • deepsense.ai, Inc.
  • 2100 Geng Road, Suite 210
  • Palo Alto, CA 94303
  • United States of America
  • deepsense.ai Sp. z o.o.
  • al. Jerozolimskie 44
  • 00-024 Warsaw
  • Poland
  • ul. Łęczycka 59
  • 85-737 Bydgoszcz
  • Poland
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