Linear Algebra for AI - Generative AI

Master Linear Algebra: Essential Math for AI , Data Science, Machine Learning, and Deep Learning Applications

What you'll learn
Build Mathematical intuition required for Data Science and Machine Learning
The linear algebra intuition required to become a Data Scientist
How to take their Data Science career to the next level
Hacks, tips & tricks for their Data Science career
Implement Machine Learning Algorithms better
Apply Linear Algebra in Data Analysis
Learn core concept to Implement in Machine Learning

Requirements
Pen and a paper to workout maths problem
Computer with Python to execute the code
Some programming experience

Description
Master Linear Algebra for Data Science, Machine Learning, and Deep Learning - Unleash the Power of Mathematics in AI ApplicationsAre you eager to enhance your skills in Machine Learning, Deep Learning, and Data Science by mastering the crucial foundation of Linear Algebra? Look no further – this comprehensive course is designed just for you.With the increasing demand for expertise in Machine Learning and Deep Learning, it's crucial to avoid the common mistake of relying solely on tools without a deep understanding of their underlying mathematical principles. This course is your key to developing a solid foundation in mathematics, providing you with a profound intuition of how algorithms work, their limitations, and the assumptions they rely on.Why is a strong mathematical foundation important? Understanding the machinery under the hood is the key to becoming a confident practitioner in the fields of Machine Learning, Data Science, and Deep Learning. Linear Algebra is universally acknowledged as a fundamental starting point in the learning journey of these domains.The basic elements of Linear Algebra – Vectors and Matrices – serve as the backbone for storing and processing data in various applications of Machine Learning, Data Science, and Artificial Intelligence. From basic operations to complex tasks involving massive datasets, Linear Algebra plays a pivotal role.Even in advanced technologies like Deep Learning and Neural Networks, Matrices are employed to store inputs such as images and text, providing state-of-the-art solutions to complex problems.Recognizing the paramount importance of Linear Algebra in a Data Science career, we have crafted a curriculum that ensures you build a strong intuition for the concepts without getting lost in complex mathematics.By the end of this course, you will not only grasp the analytical aspects of Linear Algebra but also witness its practical implementation through Python. Additionally, you will gain insights into the functioning of the renowned Google PageRank Algorithm, utilizing the concepts learned throughout the course.Here's what the course covers:Vectors BasicsVector ProjectionsBasis of VectorsMatrices BasicsMatrix TransformationsGaussian EliminationEinstein Summation ConventionEigen ProblemsGoogle Page Rank AlgorithmSVD - Singular Value DecompositionPseudo InverseMatrix DecompositionSolve Linear Regression using Matrix MethodsLinear Regression from ScratchLinear Algebra in Natural Language ProcessingLinear Algebra for Deep LearningLinear Regression using PyTorchBonus: Python Basics & Python for Data ScienceThis hands-on course takes you on a step-by-step journey, providing the essential Linear Algebra skills required for Data Science, Machine Learning, Natural Language Processing, and Deep Learning. Enroll now and embark on your journey to master the mathematical foundations powering AI applications. Click the 'Enroll' button to start your learning experience – I look forward to seeing you in Lecture 1!

Who this course is for:
Data Scientists who wish to improve their career in Data Science., Machine Learning Practitioners, Any one who wants to understand the underpinnings of Maths in Data Science, Machine Learning and Artificial intelligence, Any Data Science enthusiast, Any student or professional who wants to start or transition to a career in Data Science., Students who want to refresh and learn important maths concepts required for Machine Learning , Deep Learning & Data Science., Any data analysts who want to level up in Machine Learning., Any people who are not satisfied with their job and who want to become a Data Scientist.