Getting Started with Machine Learning with R
Getting Started with Machine Learning with R
Get up-and-running via Machine Learning with Python's insightful projects
About This Python Machine Learning Projects Video course
- Explore the power of Python and create your own machine learning models with this project-based tutorial
- Get superb insights from your data in different scenarios and deploy machine learning models with ease
- Learn how to put complex machine learning concepts into practice
Python Machine Learning Projects In Detail
Machine learning gives you unimaginably powerful insights into data. Today, implementations of machine learning have been adopted throughout Industry and its concepts are numerous. This video course is a unique blend of projects that teach you what Machine Learning is all about and how you can implement machine learning concepts in practice.
Six different independent projects will help you master machine learning in Python.
The video will cover concepts such as classification, regression, clustering, and more, all the while working with different kinds of databases. By the end of the course, you will have learned to apply various machine learning algorithms and will have mastered Python's packages and libraries to facilitate computation. You will be able to implement your own machine learning models after taking this course.
What will you learn in this course?
Course plan
Chapter 1
Build an App to Find Cheap Airfares
Build an App to Find Cheap Airfares
Chapter 2
Forecast the IPO Market Using Logistic Regression
Forecast the IPO Market Using Logistic Regression
Chapter 3
Create a Custom Newsfeed
Create a Custom Newsfeed
Chapter 4
Forecasting the Stock Market with Machine Learning
Forecasting the Stock Market with Machine Learning
Chapter 5
Build an Image Similarity Engine
Build an Image Similarity Engine
Chapter 6
Building a Chatbot
Building a Chatbot
Detailed course plan
Chapter 1 : Build an App to Find Cheap Airfares
34m46
Lesson 1The Course Overview
Lesson 2Sourcing Airfare Pricing Data
Lesson 3Retrieving the Fare Data with Advanced Web Scraping Techniques
Lesson 4Parsing the DOM to Extract Pricing Data
Lesson 5Sending Real-Time Alerts Using IFTTT
Lesson 6Putting It All Together
Chapter 2 : Forecast the IPO Market Using Logistic Regression
32m19
Lesson 1The IPO Market
Lesson 2Feature Engineering
Lesson 3Binary Classification
Lesson 4Feature Importance
Chapter 3 : Create a Custom Newsfeed
35m56
Lesson 1Creating a Supervised Training Set with the Pocket App
Lesson 2Using the embed.ly API to Download Story Bodies
Lesson 3Natural Language Processing Basics
Lesson 4Support Vector Machines
Lesson 5IFTTT Integration with Feeds, Google Sheets, and E-mail
Lesson 6Setting Up Your Daily Personal Newsletter
Chapter 4 : Forecasting the Stock Market with Machine Learning
30m12
Lesson 1What Does Research Tell Us about the Stock Market?
Lesson 2Developing a Trading Strategy
Lesson 3Building a Model and Evaluating Its Performance
Lesson 4Modeling with Dynamic Time Warping
Chapter 5 : Build an Image Similarity Engine
26m36
Lesson 1Machine Learning on Images
Lesson 2Working with Images
Lesson 3Finding Similar Images
Lesson 4Building an Image Similarity Engine
Chapter 6 : Building a Chatbot
16m40
Lesson 1The Design of Chatbots
Lesson 2Building a Chatbot
