Trading with Machine Learning: Classification and SVM
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- Live Trading
- Learning Track
- Prerequisites
- Syllabus
- About author
- Testimonials
- Faqs
Live Trading
- Explain the concept of Support Vectors
- Explain what a hyperplane is
- Use cross-validation to tune the hyper-parameters of a support vector machine
- Code a trading strategy to predict the next day's trend using a Support Vector Classifier
- Paper trade and analyze the strategies and apply in live markets without any installations or downloads

Skills Covered
learning track 4
This course is a part of the Learning Track: Machine Learning & Deep Learning in Trading Beginners
Course Fees
Full Learning Track
These courses are specially curated to help you with end-to-end learning of the subject.
Course Features
- Community
Faculty Support on Community
- Interactive Coding Exercises
Interactive Coding Practice
- Trade & Learn Together
Trade and Learn Together
- Get Certified
Get Certified
Prerequisites
Prior experience in programming is required to fully understand the implementation of machine learning algorithm taught in the course. However, Python programming knowledge is optional. If you want to be able to code and implement the machine learning strategies in Python, then you should be able to work with 'Dataframes'. These skills are covered in the course 'Python for Trading'. Basic knowledge of machine learning algorithms and train and test datasets is a plus. These concepts are covered in our free course: Introduction to Machine Learning.
Syllabus
- IntroductionThis section presents the topic of machine learning classification, along with its types and applications. It covers technical indicators such as RSI, Parabolic SAR, and ADX.Getting StartedQuantra Features and GuidanceWhat is Classification?Steps to ClassifyTeaser on ClassificationTypes and ApplicationsTechnical ReferencesImporting LibrariesTechnical Indicators - Part AKnow Your Technical IndicatorsTechnical Indicators - Part BApplying Technical IndicatorsDropping ValuesCreating An IndicatorRecap
Binary Classification
- Multiclass Classification
- Support Vector Machine
- Prediction and Strategy
- Live Trading on Blueshift
- Live Trading Template
- Live Trading on IBridgePy
- Paper and Live Trading
- Run Codes Locally on Your Machine
- Downloadable Resources
Why quantra®?
- More in Less Time
Gain more in less time
- Expert Faculty
Get taught by practitioners
- Self-paced
Learn at your own pace
- Data & Strategy Models
Get data & strategy models to practice on your own
Faqs
- When will I have access to the course content, including videos and strategies?
You will gain access to the entire course content including videos and strategies, as soon as you complete the payment and successfully enroll in the course.
- Will I get a certificate at the completion of the course?
- Are there any webinars, live or classroom sessions available in the course?
- Is there any support available after I purchase the course?
- What are the system requirements to do this course?
- What is the admission criteria?
- Is there a refund available?
- Is the course downloadable?
- Can the python strategies provided in the course be immediately used for trading?
- I want to develop my own algorithmic trading strategy. Can I use a Quantra course notebook for the same?
- If I plug in the Quantra code to my trading system, am I sure to make money?
- Do you need to have knowledge of coding in order to learn through Quantra courses?
- What does "lifetime access" mean?