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Artifical Inteliegence & Machine Learning --

 Machine learning is a subfield of artificial intelligence, which is broadly defined as the capability of a machine to imitate intelligent human behavior. Artificial intelligence systems are used to perform complex tasks in a way that is similar to how humans solve problems. While artificial intelligence encompasses the idea of a machine that can mimic human intelligence, machine learning does not. Machine learning aims to teach a machine how to perform a specific task and provide accurate results by identifying patterns.

What will you learn in the Workshop?🤔

Day 1: Machine Learning Fundamentals and topics

  1. Introduction to Machine Learning
    • Definition, history, and applications
    • Types of ML (supervised, unsupervised, reinforcement)
  2. Data Preprocessing and Visualization
    • Data cleaning and preprocessing
    • Data visualization tools (Matplotlib, Seaborn)
  3. Machine Learning Algorithms
    • Linear Regression
    • Decision Trees
    • Random Forest
  4. Hands-on Exercise: Implementing ML Algorithms
    • Deep Learning Fundamentals
    • Natural Language Processing (NLP)
    • Case Studies: ML in Industry
    • Hands-on Exercise: Building an NLP Model

Day 2: Artificial Intelligence and Advanced ML

  1. Introduction to Artificial Intelligence
    • Definition, history, and applications
    • Types of AI (narrow, general, superintelligence)
  2. Computer Vision
    • Image processing
    • Object detection
    • Image segmentation
  3. Reinforcement Learning
    • Markov Decision Processes (MDPs)
    • Q-learning
    • Policy gradients
  4. Hands-on Exercise: Building a Computer Vision Model
    • Advanced ML Topics
    • AI Ethics and Fairness
    • Future of AI and ML

What students learn?📝

 The ML & AI workshop with immense curiosity and enthusiasm. The workshop exceeded my expectations, providing a comprehensive understanding of ML & AI concepts, applications, and hands-on experience.

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