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+ 38

# Prerequisites for machine learning ?

What things I should know before learning machine learning ?

20 Answers

+ 14

Math is important. A course in linear algebra can be very helpful. Still, you don't have to know the math behind everything to use machine learning in practice.
Just having a good foundation in python and some experience with data handling libraries like pandas or even with numpy is enough to get you started.
I will recommend you this way, get familiar with python and numpy first. Take some course or buy a book (Hands-on Machine Learning with Scikit-learn and Tensorflow by Aurelion Geron is awesome). You can study math later to gain some intuition of algorithms. But personally, I don't think high level math is necessary before starting with machine learning.
Hope that helps!
:)

+ 11

https://www.sololearn.com/Discuss/1175584/?ref=app
And for the other guy who copied a full answer from Quora without any link or quote of reference:
https://www.quora.com/Which-mathematical-concepts-or-subjects-should-I-learn-as-a-beginner-to-machine-learning-or-data-science

+ 10

According to me, maths (especially algebra), knowing intro level of Python will be fine for one who is just getting started with learning ML.Moreover, knowing MATLAB will also do good as I had used it in one of my college projects which involved AI.

+ 9

Linear algebra intro:
https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab

+ 8

Math, coding and willingness to learn new concepts.

+ 8

M A T H

+ 6

According to me Math is the important thing for the machine learning and you also have basic and conceptual knowledge of python because programming in machine learning are coded in the python. before dive in machine learning knowledge of the following is necessary
1. Linear algebra.
2. Calculus.
3. Probability theory.
4. Programming.
5. Optimization theory.
http://pythonandmltrainingcourses.com/6-months-training-in-noida/

+ 5

Statistics, Mathematics i.e Algebra, Calculus & Probability, Python and or R languages or any other programming language you feel okay with.

+ 5

Being an Electronics Engineering student I consider above scenario as the electronics enthusiast makes projects using an Arduino but fails to appreciate the real Electronics of how microcontroller works, similarly when you are using Python Libraries for ML, you may build huge models but it may happen that you will not able to appreciate the real beauty of ML. Thus, start learning without delay but make yourself so that you should be able to appreciate the science and actual things happening behind the real Machine Learning!
Don't wait for the things you want to learn!

+ 3

Well if we divide those prerequisites into categories we have:
Mathematics:
you should know multi-variable calculus, As a matter of fact, there are some concepts that you see a lot in machine learning fields such as gradians and derivatives and integrals.
aside from calculus, you should know Linear Algebra,
concepts like vectors and Matrices are used a lot in machine learning.
discrete mathematics is not a prerequisite but can help you think differently.
Probability and Statistics are important, especially if you are willing to pursue a data analysis field.
other than mathematics, having a basic knowledge of algorithms and data structures is obligatory.
and as you may know, the two popular languages used for Machine Learning
are Python and R, so start learning one!
I personally suggest python.
after you learnt the basics, you should learn a framework like numPy, Torch and TensorFlow.
I suggest that you learn numPy first because it's very popular and multi-purpose.
after that use PyTorch for your projects and ideas.
once you got the hang of Machine Learning you can learn TensorFlow and that's because learning TensorFlow is a bit harder and takes more time to master.

+ 3

I think the interest is the most important thing you needed

+ 2

In short, u need to have data analysis and visualization skills

+ 2

Before starting machine learning you should have a good base of mathematical concepts like statistics and probability, linear algebra, calculus and matrices.
You can try Khan academy courses to get all of these.
After being comfortable with them you could start learning a language popular for machine learning - python, R or matlab. BTW many people recommends python because of its libraries and it's community.
After mastering a language just refer to some algorithms and learn about them if necessary.
And finally! take a ML course. There are many good courses in datacamp, kaggle, springboard, coursera. I encourage you to check all of them and find the best fit for you.
NOTE: Datacamp also provide Python and R courses specifically designed for data science.
Hope this answer helps

+ 2

Linear algebra, calculus, statistics + Python (Scikit or Tensorflow) and a lot of willingness to learn!

+ 2

Short Answer:
1.Probability(Main)
2.Linear Algebra(Main)
3.Statistics
4.Familiar with Deterministic Coding(Optional)
5.Python, IDEs and Available Libraries (mostly used ones)
Long Answer:
You can start simulating and creating ML models without any prerequisite but , .... , When it comes to understanding the things behind the scenes you need to have solid foundation!
Let me tell you simple example, nearly a month back I have attended a workshop on ML / AI / DL with Python , Instructor started with hello world of ML i.e. Iris Dataset consists of 3 species of iris(flower) with some features, and some ML models were used to classify according to features and regression analysis was done with some models, now in this scenario you may get superficial idea(satisfaction) of getting started with ML but deep down you will be wondering how on earth the regression/classification happened, if you don't have string grasp on previously mentioned fundamentals!

+ 1

Study pc organization

0

No it is a very heart

0

Before learning the hot machine learning you just need to remember that you have learnt in you higher school that is some mathematics which includes linear algebra,probability also the programming this will help you to <a href="http://pythonandmltrainingcourses.com/courses/best-machine-learning-course-in-delhi/
">learn Machine learning easilyl</a>

0

It depends on how much you want to understand the underlying basis of the algorithms but as far as theoretical knowledge is concerned, I would recommend some probability and statistics in any case as well as a primer on data science / machine learning that will tell you e.g. the difference between supervised and unsupervised learning, so forth. Calculus and linear algebra can give you deeper understanding but for most applications aren't strictly necessary. Probability and statistics on the other hand is vital for evaluating model output and ensuring proper input.

- 2

Dbms, DBS, DNS, R, python, I & T,
AI, & RDBMS are necessary subjects along with programming languages expertise for machine learning.
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