How to become a Machine Learning Engineer?

1. Learn a Programming Language :

Popular Programming Languages for Machine Learning

R
Matlab
SAS
Python
WEKA
Excel

If you go with Python, you must learn sklearn for Machine Learning. Sklearn is a modern machine learning library written …


This content originally appeared on DEV Community and was authored by SOMYA RAWAT

1. Learn a Programming Language :

Popular Programming Languages for Machine Learning

  • R
  • Matlab
  • SAS
  • Python
  • WEKA
  • Excel

If you go with Python, you must learn sklearn for Machine Learning. Sklearn is a modern machine learning library written in Python.

2. Learn Mathematics for Machine Learning :

Importance of Mathematics topics needed for Machine Learning

  • Linear Algebra - 35%
  • Probability and Statistics - 25%
  • Algorithm and Complexity - 15%
  • Calculus - 15%
  • Others - 10%

Having a basic understanding of probability and statistics is important when it comes to mastering Machine Learning.

3. Learn Core Machine Learning Algorithms :

Supervised Machine Learning :

  • Regression :
  • Linear Regression

  • Polynomial Regression

  • Decision Tree

  • Random Forest Model

  • Classification :

  • KNN

  • Trees

  • Logistic Regression

  • Naive-Bayes

  • SVM

Unsupervised Machine Learning :

  • Clustering :
  • SVD
  • PCA

  • K-Means

  • Association Analysis :

  • Apriori

  • FP-Growth

  • Hidden Markev Model

Reinforcement Machine Learning

4. Learn the basics Libraries for Mathematical and Data Handling :

  • Spark
  • Pytorch
  • Scikit-learn
  • Keras
  • Pandas
  • mxnet
  • Numpy
  • NLTK
  • TensorFlow

5. Learn Deep Learning


This content originally appeared on DEV Community and was authored by SOMYA RAWAT


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