Python Machine Learning Solutions
100 videos that teach you how to perform various machine learning tasks in the real world.
Course Description
Machine learning is increasingly pervasive in the modern datadriven world. It is used extensively across many fields such as search engines, robotics, selfdriving cars, and more.
With this course, you will learn how to perform various machine learning tasks in different environments. We’ll start by exploring a range of reallife scenarios where machine learning can be used, and look at various building blocks. Throughout the course, you’ll use a wide variety of machine learning algorithms to solve realworld problems and use Python to implement these algorithms.
You’ll discover how to deal with various types of data and explore the differences between machine learning paradigms such as supervised and unsupervised learning. We also cover a range of regression techniques, classification algorithms, predictive modelling, data visualization techniques, recommendation engines, and more with the help of realworld examples.
Learning Outcomes
Explore classification algorithms and apply them to the income bracket estimation problem
Use predictive modeling and apply it to realworld problems
Understand how to perform market segmentation using unsupervised learning
Explore data visualization techniques to interact with your data in diverse ways
Find out how to build a recommendation engine
Understand how to interact with text data and build models to analyze it
Work with speech data and recognize spoken words using Hidden Markov Models
Analyze stock market data using Conditional Random Fields
Work with image data and build systems for image recognition and biometric face recognition
Grasp how to use deep neural networks to build an optical character recognition system
Prerequisite
This course is friendly to Python beginners, but familiarity with Python programming would certainly be useful to play around with the code.
Who is this course intended for?
This video is for Python programmers who are looking to use machinelearning algorithms to create realworld applications. This course is friendly to Python beginners, but familiarity with Python programming would certainly be useful to play around with the code.
These independent videos teach you how to perform various machine learning tasks in different environments. Each of the video in the section will cover a reallife scenario.
Course Curriculum
The Realm of Supervised Learning
Available in
days
days
after you enroll

PreviewPreprocessing Data Using Different Techniques (4:09)

StartLabel Encoding (6:04)

StartBuilding a Linear Regressor (2:25)

StartRegression Accuracy and Model Persistence (4:25)

StartBuilding a Ridge Regressor (3:41)

StartBuilding a Polynomial Regressor (2:40)

StartEstimating housing prices (2:32)

StartComputing relative importance of features (3:45)

StartEstimating bicycle demand distribution (1:54)
Constructing a Classifier
Available in
days
days
after you enroll

PreviewBuilding a Simple Classifier (3:40)

StartBuilding a Logistic Regression Classifier (4:50)

StartBuilding a Naive Bayes’ Classifier (2:11)

StartSplitting the Dataset for Training and Testing (1:23)

StartEvaluating the Accuracy Using CrossValidation (4:06)

StartVisualizing the Confusion Matrix and Extracting the Performance Report (4:13)

StartEvaluating Cars based on Their Characteristics (5:11)

StartExtracting Validation Curves (2:49)

StartExtracting Learning Curves (1:37)

StartExtracting the Income Bracket (3:36)
Predictive Modeling
Available in
days
days
after you enroll

PreviewBuilding a Linear Classifier Using Support Vector Machine (4:23)

StartBuilding Nonlinear Classifier Using SVMs (1:46)

StartTackling Class Imbalance (2:53)

StartExtracting Confidence Measurements (2:36)

StartFinding Optimal HyperParameters (2:16)

StartBuilding an Event Predictor (3:45)

StartEstimating Traffic (2:39)
Frequently Asked Questions
When does the course start and finish?
The course starts now and never ends! It is a completely selfpaced online course  you decide when you start and when you finish.
How long do I have access to the course?
How does lifetime access sound? After enrolling, you have unlimited access to this course for as long as you like  across any and all devices you own.
What if I am unhappy with the course?
We would never want you to be unhappy! If you are unsatisfied with your purchase, contact us in the first 30 days and we will give you a full refund.