Python for Data Science - Machine Learning

Python for Machine Learning

Python for Data Visualization

Libraries

Matplotlib

Seaborn

ggplot

GraphX

Plotly

Functions

Exploratory data analysis

Data storytelling

Decision-support dashboard design

Public education(news, media, and data blogging)

Python for Machine Learning

Libraries

scikit-learn

Tensor Flow

PyTorch

Functions (By Use Case)

Regression

Clustering

Dimension reduction

Association rules

Deep learning

Instance-based

Decision trees

Bayesian

Ensemble

Regularization

Python for Data Engineering

Functions

• Learn to build simple MapReduce jobs (sans Java)
• Write Spark jobs(sans Scala)
• Programming IoT device(Raspberry Pi)
• Building ETL processes(Airflow)

Types of Machine Learning Methods

Supervised Learning	Making predictions straight from labeled data
Unsupervised Learning	Making predictions straight from unlabeled data
Semi-Supervised Learning	Uses both labeled and unlabeled data to make a set of predictions

Popular Ways to Group ML Algorithms

By Learning	By Function	By Use Case
Supervised	Regression	Fraud detection
Unsupervised	Clustering	Recommendation engines
Semi-supervised	Dimension reduction	Price forecasting
	Association rules	Inventory demand forecasting
	Deep learning	Water consumption forecasting
	Instance-based	Infrastructure demand forecasting
	Decision trees	And so on
	Bayesian
	Ensemble
	Regularization