Machine Learning using Python Training

Answers to Popular Questions:

 
Yes, this class can be tailored to meet your specific training needs.
Yes, we provide Python consulting services.
Yes, group discounts are provided.

Course Description

 
This class employs the Python modules Matplotlib, Scipy and Numpy, Pandas, Sklearn and the IPython to explore a variety of different Machine Learning algorithms. Students will gain an in depth knowledge of Advanced Python constructs and a basic understanding of Machine Learning.
Course Length: 3 Days
Course Tuition: $1790 (US)

Prerequisites

Students must have an intermediate knowledge of Python that includes classes and objects, lists, tuples, reading from a file ...

Course Outline

 

iPython
About iPython
Features of iPython
Starting iPython
Tab completion
Magic commands
Benchmarking
External commands
Enhanced help
Notebooks

numpy
Python’s scientific stack
numpy overview
Creating arrays
Creating ranges
Working with arrays
Shapes
Slicing and indexing
Indexing with Booleans
Stacking
Iterating
Tricks with arrays
Matrices
Data types
numpy functions

scipy
About scipy
Polynomials
Vectorizing functions
Subpackages
Getting help
Weave

A Tour of scipy subpackages
cluster
constants
fftpack
integrate
interpolate
io
linalg
ndimage
odr
optimize
signal
sparse
spatial
special
stats

pandas
About
pandas
Pandas architecture
Series
DataFrames
Data Alignment
Index Objects
Basic Indexing
Broadcasting
Removing entries
Time series
Reading Data

matplotlib
About matplotlib
matplotlib architecture
matplotlib Terminology
matplotlib keeps state
What else can you do?

Basics of Machine Learning

Definition of machine learning
Types of machine learning
Machine learning implementation examples

Machine Learning using Sclearn

Machine learning: the problem setting
Loading an example dataset
Learning and predicting
Model persistence
Conventions
Data Visualization using padas, matplotlib and seaborn

 

 

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