Machine Learning in simple words, is all about making the computers to perform intelligent tasks without explicitly coding. This is achieved by training the computer with lots of data.
For example: Detecting whether a mail is spam or not, recognizing handwritten digits, Fraud detection in Transactions. etc..,
Math Skills:
Probability and Statistics :
Machine learning is very much closely related to statistics.
You need to know the fundamentals of statistics and
probability theory,descriptive statistics, Baye's rule and
random variables, probability distributions,sampling,
hypothesis testing, regression and decision analysis.
Linear Algebra:
You need to know working with matrices and some
basic operations on matrices such as matrix addition,
subtraction, scalar and vector multiplication, inverse,
transpose and vector spaces.
Calculus:
Basics of differential and integral calculus.
Programming skills:
A little bit of coding skills is enough. But its preffered
to have the knowledge of data structures, algorithms and OOPs
concepts.
Some of the popular programming languages to learn is Python,
R, Java and C++.
Its your preference to master any one programming language. But
its advisable to have a little understanding of other languages
and what their advantages and disadvantages are over your
preffered one.
Data engineer skills:
Ability to work with large amounts of data (big data),Data
preprocessing, knowledge of SQL and NoSQL, ETL (Extract transfor
Load), data analysis and visualization skills.
Knowledge of Machine Learning Algorithms:
Should be familiar with popular machine learning algorithms such
as linear regression, logistic regression, decision trees,
random forest, clustering (K means, heirarchichal), reinforcement
learning and neural networks.
Knowledge of Machine Learning Frameworks:
Familiar with popular machine learning frameworks such as scikit
learn, tensorflow, Azure, caffe, theano, spark and torch.