Intermediate AI/ML

But what is a neural network? | Deep learning chapter 1

The Essential Main Ideas of Neural Networks

Transformers Explained - How transformers work

Learn AI, Machine Learning, Deep Learning and Generative AI Explained

How AI Image Generators Work (Stable Diffusion / Dall-E) - Computerphile

Transformer Neural Networks - EXPLAINED! (Attention is all you need)

Illustrated Guide to Transformers Neural Network: A step by step explanation

Learn Machine Learning Like a GENIUS and Not Waste Time

All Machine Learning algorithms explained in 17 min

Learn What is YOLO algorithm? | Deep Learning Tutorial 31 (TensorFlow, Keras & Python)

Natural Language Processing: Crash Course AI 7

Lets learn basics to transform your career. I promise not to exhaust you with huge number of videos.Artificial Intelligence, Machine Learning, Data Science are the most hot skills in the markets which has potential to help you earn highest salary. These skills has potential to turn your financial to better level which can provide you growth and prosperity. Welcome to the most comprehensive Introduction to AI, Machine Learning and Data Science course! An excellent choice for beginners and professionals looking to expand their knowledge on Artificial Intelligence, Machine Learning, Data Science, Deep Learning, Supervised and Unsupervised Learning. This is an introductory course for beginners to boost your knowledge. This course gives introduction to to AI, Machine Learning, Data Science, Deep Learning, Supervised and Unsupervised learning with real time examples where machine learning can be applied to solve or simplify real world business problems.What you'll learn Introduction to buzz words like AI, Machine Learning, Data Science and Deep Learning etc.Real time examples where Machine Learning can be used to solve real world business problems Introduction to Supervised Learning and Unsupervised Learning Introduction to Natural Language Processing Why python is popular for Machine Learning Prerequisite: You just need computer or mobile phone with internet connection to access course material.No prerequisites !Happy Learning!

This is a top selling Machine Learning and Data Science course just updated this month with the latest trends and skills for 2023! Become a complete Data Scientist and Machine Learning engineer! Join a live online community of 900,000+ engineers and a course taught by industry experts that have actually worked for large companies in places like Silicon Valley and Toronto. Graduates of Andrei’s courses are now working at Google, Tesla, Amazon, Apple, IBM, JP Morgan, Meta, + other top tech companies. You will go from zero to mastery!Learn Data Science and Machine Learning from scratch, get hired, and have fun along the way with the most modern, up-to-date Data Science course on Udemy (we use the latest version of Python, TensorFlow 2.0 and other libraries). This course is focused on efficiency: never spend time on confusing, out of date, incomplete Machine Learning tutorials anymore. We are pretty confident that this is the most comprehensive and modern course you will find on the subject anywhere (bold statement, we know).This comprehensive and project based course will introduce you to all of the modern skills of a Data Scientist and along the way, we will build many real world projects to add to your portfolio. You will get access to all the code, workbooks and templates (Jupyter Notebooks) on Github, so that you can put them on your portfolio right away! We believe this course solves the biggest challenge to entering the Data Science and Machine Learning field: having all the necessary resources in one place and learning the latest trends and on the job skills that employers want.The curriculum is going to be very hands on as we walk you from start to finish of becoming a professional Machine Learning and Data Science engineer. The course covers 2 tracks. If you already know programming, you can dive right in and skip the section where we teach you Python from scratch. If

Learn Machine Learning from scratch, this course for beginners who want to learn the fundamental of machine learning and artificial intelligence. The course includes video explanation with introductions(basics), detailed theory and graphical explanations. Some daily life projects have been solved by using Python programming. Downloadable files of ebooks and Python codes have been attached to all the sections. The lectures are appealing, fancy and fast. They take less time to walk you through the whole content. Each and every topic has been taught extensively in depth to cover all the possible areas to understand the concept in most possible easy way. It's highly recommended for the students who don’t know the fundamental of machine learning studying at college and university level.The objective of this course is to explain the Machine learning and artificial intelligence in a very simple and way to understand. I strive for simplicity and accuracy with every definition, code I publish. All the codes have been conducted through colab which is an online editor. Python remains a popular choice among numerous companies and organization. Python has a reputation as a beginner-friendly language, replacing Java as the most widely used introductory language because it handles much of the complexity for the user, allowing beginners to focus on fully grasping programming concepts rather than minute details. Below is the list of topics that have been covered:Introduction to Machine Learning Supervised, Unsupervised and Reinforcement learning Types of machine learning Principal Component Analysis (PCA)Confusion matrix Under-fitting &amp; Over-fitting Classification Linear Regression Non-linear Regression</

Becoming Data Science professional (Data Scientist) is a long journey and need guidance from seasoned Data Science professional (Chief Data Scientist). We are trying to manage the journey such a way that you learn right skills and in the right way. The whole concepts of the course are to make you ready for Data Science projects, mainly in Machine learning and AI projects. You will learn1. Foundation of Machine learning2. Supervised Machine learning - Regression3. Supervised Machine learning - Classifications4. Unsupervised Machine learning (Clustering, KNN, PCA)5. Text Analytics6. Time Series