Machine Learning Study Jam Workshop - GSDC-SFU Chapter (2023)

Welcome to the Machine Learning Study Jam Workshop hosted by Me, Technical Lead for the GSDC-SFU Chapter. This workshop was designed to provide participants with a comprehensive understanding of machine learning, data processing, and deep learning through a series of four informative and interactive sessions.

Table of Contents

• Overview
• Sessions
  • Session 1: Data Processing and Introduction to ML
  • Session 2: ML Algorithms, Feature Engineering, and Intro to Deep Learning
  • Session 3: Deep Learning and Applications
  • Session 4: Deep Learning Project - Human Emotion Detection
• Code and Materials

Overview

In this workshop, participants embarked on a journey through the realms of machine learning and deep learning, starting from foundational concepts to practical applications. The workshop was divided into four enlightening sessions, each building upon the knowledge gained in the previous one. The ultimate objective was to empower participants with the skills and understanding necessary to engage with machine learning projects confidently.

Sessions

Session 1: Data Processing and Introduction to ML

In the first session, participants were introduced to the fundamentals of data processing, including data cleaning, transformation, and analysis. Additionally, they gained insights into machine learning concepts and explored essential libraries such as Pandas, NumPy, and scikit-learn.

Session 2: ML Algorithms, Feature Engineering, and Intro to Deep Learning

In this session, participants delved into the world of machine learning algorithms, understanding their applications and workings. Feature engineering, a critical aspect of building effective machine learning models, was also covered. The session concluded with an introduction to deep learning, setting the stage for the following sessions.

Session 3: Deep Learning and Applications

The third session centered on deep learning, a pivotal component of modern AI. Participants were introduced to deep learning concepts, architectures, and applications, particularly focusing on Computer Vision (CV) and Natural Language Processing (NLP).

Session 4: Deep Learning Project - Human Emotion Detection

The final session showcased a real-world deep learning project on human emotion detection. Participants gained hands-on experience with custom model architecture, object detection (faces), image classification, and the implementation of ResNet. The project aimed to detect emotions using computer vision techniques and provided an insightful culmination to the workshop.

Code and Materials

All the materials and code for this workshop were meticulously created by Vaibhav Saini, the technical lead for the GSDC-SFU Chapter 2022-2023. However, it's important to note that the datasets, images, and other external resources used in the workshop are not owned by me and were utilized for educational purposes. The focus was on imparting knowledge and practical skills related to machine learning and deep learning. Participants were encouraged to further explore and use these skills for their personal and professional growth.

Feel free to explore and utilize the resources to enhance your understanding of machine learning and showcase your capabilities.

Thank you for being a part of this enriching Machine Learning Study Jam Workshop! For any further inquiries or collaboration opportunities.