ML Study Jam - Week 1: Introduction to Machine Learning

We'll start with an overview of how machine learning models work and how they are used. This may feel basic if you've done statistical modeling or machine learning before. Don't worry, we will progress to building powerful models soon.

Aug 17, 2023, 5:00 – 6:00 PM

270
RSVP'd

Key Themes

AIKaggleMachine Learning

About this event

ML Study Jam is a collective learning program helping community members to grow as ML practitioners. The idea is to go through basic ML concepts and share the knowledge in a community. By honing skills and enhancing capabilities, a beginner can start one’s journey to becoming an ML expert. πŸ€– πŸš€

This track is a study program going through Kaggle Learn courses. The goal of these assignments is to cover the most essential skills rapidly. Such as how to use TensorFlow or Pandas and how to build your first Machine Learning model and participate in your first competition πŸ‘ πŸŽ‰.

Kaggle is the world’s largest data science and machine learning community. It offers a no-setup, customizable Jupyter Notebooks environment, access to free GPUs, and a huge repository of community-published data & code.

"Intro to Machine Learning" is the first session of a series of 5 sessions :

Intro to Machine Learning

Intermediate Machine Learning

Intro to Deep Learning

Time Series

NLP ( Bonus session )

In this first session, we are going to cover the content based on Kaggle's micro-course "Intro to Machine Learning":

How Models Work

Basic Data Exploration

Your First Machine Learning Model

Model Validation

Underfitting and Overfitting

Random Forest

Machine Learning Competitions

For more details, you can check it out below πŸ‘‡

https://www.kaggle.com/learn/intro-to-machine-learning

Requisites:

1. Have access to a Browser (preferably Google Chrome)

2. Sign up to Kaggle

3. Eager to Learn !!!

4. Have Completed the 🐼 Pandas microcourse 

Speakers

  • Ngesa Marvin

    Founder, Nairobi AI | Arm AI Ambassador

  • Philomena Mbura

    Data Scientist | WTM Ambassador

  • Brayan Kai Mwanyumba

    She Code Africa Nairobi

    Technical Writer

  • Daisy Okacha

    Data scientist

Hosts

  • Wayne Gakuo (GDE)

    Sky.Garden

    Frontend Engineer

  • Marvin Ngesa

    Device Manager - Cloud Data & AI, Safaricom PLC

    Diffusion Models with KerasCV

  • Daisy Okacha

    Data scientist

Organizers

  • Louise Mercy Jillo

    Interswitch Group

    Organizer - Party & Happiness

  • Tabitha Kavyu

    Organizer - Communications & Crew

  • Wayne Gakuo

    Sky.Garden

    GDG Co-organizer & Crew

  • Ngesa Marvin

    Safaricom PLC

    Organizer - Strategic Partnerships, Content & ML

  • Cynthia Kamau

    Software Engineer | Programs Lead | WTM Ambassador

  • daisy okacha

    Partnerships & ML Organizer

  • Rachael Kimberly Msabeni

    WTM Ambassador

    UX Developer

  • Velda Kiara

    Organizer - Media and Blogs

  • Philomena Mbura

    WTM Ambassador

    Data Analyst/Scientist

  • Irene Onyango

    Organizer

  • Brian Ouma

    GDG Organizer

    Media & Designs

  • Teresia Kirung'o

    Organizer - Media & Communication

  • Wangari Njeri

    Organizer - Media & Communication

  • Marjan Hussein

    Organizer - Demo Zones

  • Brayan Mwanyumba

    GDG Co-Lead & Crew

  • prisca akinyi

    Hyapak

    Organizer - Partners

  • Reuben Kihiu

    Safaricom

    Product Designer