42 steps of machine learning
by saurabh kamble

1. 7 Steps to Understanding Deep Learning
1.1. Step: Introducing Deep Learning
1.2. Step : Getting Technical
1.3. Step : Backpropagation and Gradient Descent
1.4. Step : Getting Practical
1.5. Step : Convolutional Neural Nets and Computer Vision
1.6. Step : Recurrent Nets and Language Processing
1.7. Step : Further Topics
2. 7 Steps to Mastering SQL for Data Science
2.1. Step : Relational Database Basics
2.2. Step : SQL Overview
2.3. Step : Selecting, Inserting, Updating
2.4. Step : Creating, Dropping, Deleting
2.5. Step : Views and Joins
2.6. Step : SQL for Data Science
2.7. Step : SQL Integration with Python, R
3. 7 Steps to Understanding NoSQL Databases
3.1. Step : Why NoSQL?
3.2. Step : NoSQL Basics
3.3. Step : Understanding Key-value Stores
3.4. Step : Understanding Document Stores
3.5. Step : Understanding Column-oriented Databases
3.6. Step : Understanding Graph Databases
3.7. Step : Bringing it All Together
4. 7 Steps to Mastering Data Preparation with Python
4.1. Step : Preparing for the Preparation
4.1.1. Steps for Data preparation :
4.1.2. 1) Data wrangling: Convert raw data to meaning full data with following tools. 2) Python library for pandas.
4.1.3. 3) converting the data into "Data sink"
4.2. Step : Exploratory Data Analysis
4.2.1. Its a approach to analysis Data sets