ML Notes for CS and AIML or DS Students

Summary:

Machine learning is an evolving technology that enables computers to autonomously learn from past data and experiences. It has revolutionized tasks such as image recognition, speech recognition, and email filtering. It primarily employs three types of learning: Supervised, Unsupervised, and Reinforcement learning. Supervised learning uses labelled data to make predictions, while Unsupervised learning works with unlabeled data to find hidden patterns. Reinforcement learning operates through feedback mechanisms to improve performance. The effectiveness of machine learning depends on the quality and quantity of data provided, with better data leading to more accurate models.

The technology was initially conceptualized by Arthur Samuel in 1959 and has become an intersection of computer science and statistics. A typical machine learning system builds prediction models from historical data and refines these models when exposed to new data. This makes machine learning data-driven and allows it to improve performance autonomously.

In the real world, machine learning plays a crucial role in solving problems too complex for humans to address manually, especially given the massive amount of data we generate. For instance, it powers Netflix’s recommendation system and aids in cyber fraud detection. A cost function measures the algorithm’s performance, and the goal is to minimize this cost function to improve accuracy.

The machine learning life cycle consists of seven steps: Gathering Data, Data Preparation, Data Wrangling, Data Analysis, Model Training, Model Testing, and Deployment. Gathering Data involves identifying various data sources and collecting data from them. Data Preparation involves randomizing and organizing this data, followed by Data Wrangling, which cleans and transforms the data into a usable format. The machine learning system is then trained and tested using this data before deployment.

Excerpt:

ML Notes for CS and AIML or DS Students

Unit-1 – Machine Learning

Machine learning is a growing technology that enables computers to learn automatically from past data. Machine learning uses various algorithms for building mathematical models and making predictions using historical data or information. Currently, it is being used for various tasks such as image recognition, speech recognition, email filtering, Facebook autotagging, recommender system, and many more.