This question is asked many times with interest but this is one of the most evolving fields. You have to be mature in accepting new technology. Although there is not any initial point where to start machine learning.
It is a highly demanding job after digital marketing indeed, there are many things and mathematical terms for understanding the basic algorithms.
You might know everything that how a specific machine learning works. At some stage you would feel you know nothing – it’s the beauty of data science. Use social media as a tool for interest deeper inside your specific niche like data mining that is related to machine learning.
How to Change Career to Machine Learning
Do you know how a programming language works in some syntax like python, it is a good sign for taking part in data science.
Develop a daily habit of reading to take the initial step to understand how deep learning works in some eras like medicine, sentimental analysis, and education.
One Effective resource to learn how much mathematics works in the deep learning model. Follow some blogs to turn on the updates of some blogs like towardsdatascience.com for deep dive into knowledge. Understand the datasets, learn about features, read from the Kaggle website, and many more. You can also visit the library for some books. Reading books is a habit that is key to success in a career in data science. Why I used the term “data science” – because it is a parent term where you can go inside more details like NLP (natural language processing).
Understand Basic Machine Learning Algorithm
Datasets are the very first step to start with, choose machine learning algorithms to come in the second space. The only step to go with is to look into the steps or structures or patterns from the information that becomes useful.
Many new students usually ask whether should we go with ML or deep learning which is also called Neural Networks. The feature is automatically engineered in new deep learning models than machine learning. You have to use some basic algorithm for extracting new features.
Apart from this, you must know about the following:
(A) How Linear Regression Works
(B) How To Use Logistic Regression
(C) How To Use SVM (Support Vector Machine)
(D) How KNN Works
(E) Where To Use Random Forest
Learn Basic Mathematics
Linear Algebra, probability, statistics, and derivations are the main concepts that help to understand the working of different machine learning algorithms/models. There are many resources available like Coursera for doing and learning about mathematics that would be useful for your career.