The fine must have skills to become a Machine Learning Engineer are explained well here which may benefit you for making your future safe

Let's understand what machine learning is? In simple words, machine learning is all about making computers to perform intelligent tasks without explicitly coding. This is achieved by training the computer with lots and lots of data. For example, detecting whether a mail is a spam or not recognizing handwritten digit, fraud detection in transactions and many such applications. Now let's see what are the top five skills to get a machine learning job?

At number one we have

Math Skills under math skills we need to know the probability and statistics, linear algebra and calculus, 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, Bayes rule and random variables, probability distributions, sampling, hypothesis testing, regression, and decision analysis.

You need to know how to work with matrices and basic operations on matrices such as matrix addition, matrix subtraction, scalar, and vector multiplication, inverse, transpose, and vector spaces.

In calculus, you need to know the bank the basics of differential and integral calculus.

At number two we have

Programming Skills, a few coding skills are enough but its preferred to have knowledge of data structures algorithms and object-oriented programming or Earths concepts. Some of the popular Programming Languages to learn for Machine Learning is Python or Java and C++. It's your preference to master any one programming language but its advisable to have a little understanding of other languages and what their advantages or disadvantages are over your preferred point.

At number three we have

Data Engineer Skills the ability to work with large amounts of data or Big Data Data. Data preprocessing, the knowledge of sequel and no sequel ETL or extract transform and load operations, data analysis, and visualization skills.

Next, we have the knowledge of

Machine Learning Algorithms. You should be familiar with popular machine learning algorithms such as linear regression, logistic regression, decision trees, random forests, clustering like paintings or hierarchical clustering, reinforcement learning and neural networks. Finally, the knowledge of machine learning frameworks you should be familiar with popular machine learning frameworks such as

sci-kit learn,

tensorFlow,

Asure, Piano, Spark, and

Torch.