Lower Learning

Machine Learning, Natural Language Processing, Computer Vision, Adversarial Learning, Neural Networks, NLP

An Interactive way of learning and creating

Have you ever needed to describe someone or something in your video? Maybe mention their name on screen, what they do, combined with a cool animation?

Learn all major grammar topics through high-profile materials and lots of fun elements. QUALITY promised!

A master class to learn convex optimization for ML and its applications to different fields and areas of engineering

Hello everyone, my name is Mike Ryan. I’m an old school animator who specializes in traditional animation.

Learn about Complete Life Cycle of a Deep Learning Project. Implement different Neural networks using Tensorflow & Keras

This reprint highlights the importance of Deep Learning (DL), which has garnered significant attention in science, industry, and academia. It draws inspiration from the functioning of the human brain and the concept of learning. Unlike traditional and machine learning methods, deep learning techniques emulate the human brain's neural networks at a lower scale, allowing them to process and analyze substantial quantities of unstructured data. The remarkable proficiency of deep learning in unveiling intricate structures within extensive datasets genuinely resembles the extraordinary aptitude of the brain to recognize patterns and form complex connections. This unique characteristic allows DL to excel in modeling and solving complex problems across various scientific and technological fields. Just as the brain learns from experience, DL architectures learn through algorithms from data by adjusting numerous parameters during training to optimize their performance and accuracy. This concept of learning and adaptation is fundamental to DL's success.