ML Study Jam: Intro to Machine Learning

GDG on Campus University of Education, Winneba - Winneba, Ghana

Learn the fundamentals of machine learning in this beginner-friendly session! Understand k concepts supervised learning, model evaluation, and predictive modeling. We'll explore practical applications and build your first machine learning model using Python and kaggle to learn. Perfect for those new to ML!

Dec 2, 7:00 PMโ€‰โ€“โ€‰Jan 18, 2025, 6:54 PM (UTC)

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Key Themes

Certification Study GroupKaggleMachine LearningTensorFlow

About this event

The ML Study Jam is a collaborative learning program designed to help community members grow as machine learning practitioners. It focuses on building foundational ML skills through shared knowledge and hands-on practice. By mastering the basics, beginners can kick-start their journey to becoming ML experts. ๐Ÿค– ๐Ÿš€

This program follows the Kaggle Learn track, covering essential skills like using TensorFlow, Pandas, and building your first ML model. You'll also learn how to participate in Kaggle competitions ๐Ÿ‘ ๐ŸŽ‰.

Kaggle, the world's largest data science community, provides a beginner-friendly environment with pre-configured Jupyter Notebooks, free GPUs, and a wealth of datasets and code.

ML Study Jam: Session Series Overview

Session 1: Python Fundamentals

Session Schedule

๐Ÿ“… Day 1: Monday, 2nd December 2024

Topics:

  • Data Structures: Lists, dictionaries, tuples, sets
  • Loops: For and while loops for efficient iteration
  • Conditionals: If-else statements for smarter code

๐Ÿ“… Day 2: Wednesday, 4th December 2024

Topics:

  • Classes: Introduction to object-oriented programming
  • List Comprehension: Writing concise, efficient loops
  • NumPy: The basics of numerical computations

๐Ÿ“… Day 3: Friday, 6th December 2024

Topics:

  • Pandas: Organizing, cleaning, and analyzing data
  • Matplotlib: Visualizing insights and trends
  • Project: A mini hands-on Python project to apply all concepts



Resources to Power Your Learning:

Session 2: Introduction to Machine Learning

Topics Covered

  • Overview of ML Concepts
  • How Models Work
  • Basic Data Exploration
  • Underfitting and Overfitting

Resources

Intro to Machine Learning: https://www.kaggle.com/learn/intro-to-machine-learning)

Session 3: Introduction to Deep Learning

Topics Covered

  • Single Neuron
  • Deep Neural Networks
  • Stochastic Gradient Descent
  • Binary Classification

Resources:

Intro to Deep Learning: https://www.kaggle.com/learn/intro-to-deep-learning

Session 4: Computer Vision

Topics Covered

  • The Convolutional Classifier

Resources:

Computer Vision: https://www.kaggle.com/learn/computer-vision)

Session 5: Time Series Analysis

Topics Covered

  • Explore Time-Series Data
  • Forecasting Methods
  • Practical Applications

Resources:

Time Series: https://www.kaggle.com/learn/time-series


When

When

December 2, 2024โ€‰โ€“โ€‰January 18, 2025
7:00 PM โ€“ 6:54 PM (UTC)

Agenda

7:00 PM

Mentor

  • Richard Aikins

    Software Engineer

Facilitators

  • Dr. Stephen Oppong

    GDGoC Advisor

  • Emmanuel Kwesi Baah

    Lecturer (Lancaster University Ghana)

  • Prof. Benjamin Ghansah

    Head of Department (Agric)

  • Dr. Delali kwasi Dake

    Head Of Department (ICT)

  • Dr. Ben-Bright Benuwa

    Senior Lecturer at UEW

Moderators

  • Francis Sape

  • Kwame Amankwah Afrifa

    Co-Lead

Host

  • Derek Amewuga

    Community Engagement Lead

Partner

INFOCTESS logo

INFOCTESS

Organizers

  • George Arhin-Bonnah

    Lead

  • Kwame Amankwah Afrifa

    GenieLab

    Co-Lead

  • Richard Kweku Aikins

    Suptle

    Technical Mentor

  • Stephen Opoku Oppong

    Faculty Advisor

  • sape francis

    Event Coordinator

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