In this step by step guide for data scientists, I am going to share the baby steps for becoming successful data scientist or machine learning developer.
Step 1: Basics of Maths
Before creation, God did just pure mathematics. Then he thought it would be pleasant change to do some applied
-John Edensor Littlewood
Data Science is game of numbers; you must be aware of following maths concepts:
- Linear Algebra
Step 2: Choose programming language of your comfort
you can choose between Python, R, Java, and C/C++
Links :- https://learnxinyminutes.com/
Step 3: Learn basic libraries
- Matplotlib etc
Links :- http://www.numpy.org/
Step 4 : Data Pre-processing
Data! Data! Data!
Mostly data is of two types, Structured (tabular) and Unstructured (Text, Voice , Image).
For developing machine learning model, we largely put effort on data pre-processing rather than developing model. Approximately 80 % out of 100.
Data Processing is basically cleaning data and making it ready for model, the basic steps includes:
- Data Cleaning
- Data Integration
- Data Transformation
- Data Reduction
- Data Discretization
Step 5: Machine Learning Models……A big weapon (SKLEARN)
There are two types of Learning:
1.) Supervised Learning
Models: – Linear regression, Multi- Linear Regression, Random Forest (CART), Support Vector Machine (SVM), Logistic Regression, Navie Bayes etc.
2.) Unsupervised Learning
Models: – K-Means Clustering
Step 6: Measuring Performance of the Model and Adjusting Hyper – parameters
In my next article, I will share steps for learning deep learning and natural language processing.