Last time I’ve detail the logistic regression and so you need understand him enough maths to make those decisions, so we’ve created this model now and it seems okay it does the job that we need to optimize it, we need to make it in the best version of that model that can be, and how we do hat ? we can measure how good this model is using something and led an error function, and obviously the bigger the error function is that the worse the model is at predicting what you want to predict.
So we use calculus to find the optimal way of reducing that error function, so that takes you through very quickly the math you need and why you need it, and I’m going to show you how to learn it, one of the best books that I liked is MATHEMATICAL METHODS FOR SCIENCE STUDENTS , you can try It it’s a very well-thumbed copy, I’ve had it for years for linear algebra and calculus for machine learning, I would say this book is perfect, I hope that’s of some use to you.
Talking now about other resources, the first resources I recommend is this: THINK STATS EXPLORATORY DATA ANALYSIS IN PYTHON. It’s really accessible introduction to python and statistics. It covers a lot of what you’ll need to know for machine learning.
Second resources is a playlist in YouTube ‘’ ESSENCE OF LINEAR ALLGEBRA ‘’ he has a playlist in linear algebra there’re also one on calculus I would recommend you watch them both, they’re excellent in fact just watch everything that’s on the channel is superb
If you’re looking for a paid course then this mathematic for machine learning from coursera is very good and comprehensive course it covers linear algebra, multivariable calculus, and PCA : principal component analysis, you may need this course : PROGRAMA ESPECIALIZADO MATHEMATICS FOR MACHINE LEARNING
MIT OPEN COURSE WARE is other good resource I recommend,34 videos they’re superb watch those to give you some insight and expertise on linear algebra.
There also this Google course in machine learning ‘’ MACHINE LEARNING CRASH COUSE ‘’ is a very good introduction to ML and it uses tens flow and finally ‘’ AN INTRODUCTION TO STATISTICAL LEARNIN ‘’ is another book that I have, it’s excellent if you’re I python the sad thing is that all the applications, it’s superb get this book and you can download the book from the link below.
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