Adventurous AI Journey Ahead

Deep learning is a type of machine learning that uses multi-layered artificial neural networks to automatically learn patterns and features from vast amounts of data for complex tasks like image recognition, speech processing, and language translation It offers high accuracy by processing information in stages. Unlike traditional machine learning, it learns features directly from data without needing human-engineered feature extraction, making it powerful for unstructured data and complex problems. More on Deep Learning and Study Deep Learning  

MIT 6.100L Introduction to CS and Programming using Python, Fall 2022, by Prof Ana Bell. View full course (Source: MIT.edu , youtube.com) Lecture 1: Introduction to CS and Programming Using Python (1h video) I am starting to go through these videos. Generally, the Prof not only introduces the terms and concepts, she also helps me to remember them. Basically, I am motivated to continue attending her lectures and to find out more on Python. Good to meet such a wonderful professor and many thanks to MIT. Here’s a summary of the first lecture (but it’s better for you to attend). The Prof discusses the idea of an object in Python. Every object in Python has a specific type. The type tells Python the type of things we are allow to do with the object. Once, we have an object, we can assign it to a variable. These variables, basically bind names to objects. The = sign is an assignment, for example, var = type (5*4). The following have been discussed: Expressions involve objects and operatio...

  Do You Still Need to Learn Python in the Age of AI? (Source: MIT.edu – youtube.com) Watch this 3min video if you are curious to know. Also, read “Don’t blindly trustwhat AI tells you, says Google’s Sundar Pichai” (Source: bbc.com ) Personally, I perceive humans will have to clean up the “AI mess” in due course, just like, what we are doing now for “fossil fuels mess”. So it pays to learn the Python. More on Learning Python

Visit: What is Machine Learning (Source: Stanford.edu) This video (1.5min) explains in simple terms what machine learning is and how is it related to artificial intelligence. Visit: What is machine learning? (Source: IBM.com)

  Machine learning (ML) is a subset of artificial intelligence (AI) that enables systems to learn and improve from data without being explicitly programmed . Instead of following pre-written instructions, ML algorithms find patterns in data, make predictions or decisions, and get better at the task over time as they are exposed to more information.   More on ML

Visit: AI Glossary/ Dictionary (Source: MIT.edu) This is a valuable set of AI vocabulary to start off with. It not only defines the AI terms, it also explains their importance. It is good to keep this list handy. Learning the basic AI vocabulary can help us gain a better understanding of the complex field of AI. Also, developing AI literacy will enable us keep up with its advancement, appreciate its opportunities and challenges. Thus, putting us in a better position to balance any innovation with ethical considerations. Ultimately, we want AI to impact our society positively. Here’s another helpful glossary on basic GenAI Visit: Glossary of Term: Generative AI Basics (Source: MIT.edu)  

  Visit: What is AI (Source: IBM.com) This site provides a complete guide to AI fundamentals. It relatively easy to go through its materials on, for example, machine learning, deep learning, generative AI, AI agents and agentic AI. In addition, it gives an overview of AI history, its benefits and use cases, AI ethics and governance. Overall, this is a great resource for me to start off.