Hello everyone, let’s check out what are those five important must have skills for becoming an Machine Learning Engineer
First let’s understand what machine learning is?
In basic words, Machine Learning is tied in with making the Machines/Computers to perform human (Intelligent) activities without explicitly coding.
And, this is accomplished via preparing the Machines/Computers by feeding with lots of information data
- Detecting whether a mail is spam or not R
- Recognizing a handwritten digit
- Fraud Recognition in financial transactions and many such applications
Now let’s see the top five skills to become a Machine Learning Engineer
1. Math Skills
Your first step in the learning is to improve your math skills. Mathematics plays a very important role in helping you understand how Machine Learning & its algorithms work
Among the many concepts you need to understand, these three are the most important ones
- Probability & Statistics
- Linear Algebra
Probability and Statistics
Machine learning is very much closely related to statistics, so you need to know the fundamentals of statistics and probability theory Descriptive Statistics Bayes rule and Random variables
Probability distributions, Sampling, Hypothesis Testing, Regression and Decision analysis.
Linear Algebra has 2 main components – Matrices and Vectors
you need to know how to work with matrices and basic operations on matrices such as Matrix Addition, Matrix Subtraction, Scalar & vector multiplication, Inverse Transpose and Vector Spaces
In calculus – you need to know the basics of differential and integral calculus
2. Programming Skills
A tad of coding aptitudes is adequate, however it’s ideal to have the basic understanding on Data Structure Algorithms, Calculations and OOPs ideas (Object Oriented Programming concepts)
Here are the most popular programming Languages to learn for machine learning
Python & R are one of the mostpreffered languages when it comes to Machine Learning followed by Java & C.
However, it’s your preference to master any one programming language and it’s advisable to have a little understanding of other languages and what their advantages or disadvantages are over your preferred one
3. Data Engineering Skills
Ability to work with large amounts of Data or Big Data
Data pre-processing – the knowledge of SQL and Non-SQL, ETL (Extract Transform and Load) operations Data Analysis and Visualization skills
and knowledge about Database management software (DBMS) – SQL, ORACLE, No-SQL etc.
4. Machine Learning Algorithms
Next step is to learn Machine Learning algorithms – among many of the ML algorithms you can devide them into 2 different categories – Supervised & Unsupervised Machine Learning
Besides the Data Engineering skills, you ought to be acquainted with mainstream machine learning algorithms such as Linear regression, Logistic regression, Decision trees, Random forests
Clustering like paintings or hierarchical clustering, Reinforcement Learning and Neural Networks
5. Machine Learning Framework
Machine learning frameworks makes the life of the developers and users a whole lot easier
They help to abstract the complex part of the Machine Learning and make it available to large group of developers
Finally the knowledge of machine learning frameworks – should be familiar with popular machine learning frameworks such as SCIKIT-learn TENSORFLOW, AZURE, CAFFE,TEANO, SPARK and TORCH
In today’s time, owing to its enormous application and adaptability, the demand for Artificial Intelligence (AI) & Machine Learning (ML) have been ever INCREASING above BIG DATA and CLOUD Computing
So this a clear indication that Artificial Intelligence & Machine Learning is the future and here to stay. And the companies are ready to onboard & invest in the Machine Learning skilled Engineers !!
To understand Machine Learning in details, visit my below article: