Machine Learning and Android workshop

NITI sabhagaar, prabha bhawan, jaipur, 302017

This is a 2-hour workshop on supervised learning and data manipulation

Feb 9, 12:30 – 2:30 PM



Key Themes

AndroidMachine LearningSolution Challenge

About this event

Title: Introduction to Machine Learning Workshop


Machine Learning (ML) has become an essential tool in various fields, from business and finance to healthcare and technology. This workshop provides an introduction to the fundamentals of ML, equipping participants with the knowledge and skills to understand and apply ML techniques effectively.

During this hands-on workshop, participants will dive into the basics of ML, including supervised and unsupervised learning, classification, regression, and clustering algorithms. They will learn how to preprocess data, select features, train models, and evaluate their performance using real-world datasets.

Key Topics Covered:

1. Introduction to Machine Learning: Understand the basic concepts and principles of ML, including supervised and unsupervised learning, and the difference between regression and classification.

2. Data Preprocessing: Learn how to clean and preprocess raw data to prepare it for ML model training, including handling missing values, encoding categorical variables, and scaling features.

3. Model Selection and Evaluation: Explore different ML algorithms, such as linear regression, logistic regression, decision trees, random forests, and k-nearest neighbors. Understand how to select the appropriate model for a given task and evaluate its performance using metrics like accuracy, precision, recall, and F1-score.

4. Hands-on Exercises: Engage in hands-on exercises and coding sessions using popular ML libraries like scikit-learn and TensorFlow. Apply the concepts learned to real-world datasets and build ML models to solve classification and regression problems.

5. Best Practices and Tips: Learn best practices for ML model development, including feature engineering, hyperparameter tuning, cross-validation, and model interpretation. Discover tips for avoiding common pitfalls and improving the performance of ML models.

Who Should Attend:

- Students and professionals with a basic understanding of programming and statistics who are interested in learning about machine learning.

- Data analysts, software engineers, and researchers who want to expand their skills in ML and apply it to their work projects.

- Anyone looking to explore the exciting field of ML and its applications in various industries.

By the end of this workshop, participants will have gained a solid foundation in machine learning concepts and techniques, empowering them to tackle real-world problems and leverage the power of ML in their projects and endeavors.



Friday, February 9, 2024
12:30 PM – 2:30 PM UTC


  • Raushan Shahi


    GDSC Lead


    Marketing Lead


    Design Lead

  • Nidhi Mehta

    Google Developer Student Club (MNIT)

    Event Coordinator Lead

  • Chahat Singhal

    Technical Co-Lead


    Event Coordinator co-Lead

  • Anushka Yadav

    Marketing Co-Lead

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