Neural Network Trading Bot

Neural Network Trading Bot, available at $49.99, has an average rating of 3.55, with 56 lectures, based on 97 reviews, and has 705 subscribers.

You will learn about Building a Neural Network trading bot What is a Trading Bot Building a Trading bot from scratch Market indicators (Moving average, stop loss, stoch) Network communication using HTTP What is an API Reading the documentation and using an API Mathematics for Market Trend analysis Basics of Neural Networks Using Neural Networks for Trading Trade cryptocurrency on various crypto exchanges This course is ideal for individuals who are Students curious about Finance and Market movements or Developers curious about applying Machine learning knowledge to finance It is particularly useful for Students curious about Finance and Market movements or Developers curious about applying Machine learning knowledge to finance.

Enroll now: Neural Network Trading Bot

Summary

Title: Neural Network Trading Bot

Price: $49.99

Average Rating: 3.55

Number of Lectures: 56

Number of Published Lectures: 41

Number of Curriculum Items: 56

Number of Published Curriculum Objects: 41

Original Price: $174.99

Quality Status: approved

Status: Live

What You Will Learn

Building a Neural Network trading bot
What is a Trading Bot
Building a Trading bot from scratch
Market indicators (Moving average, stop loss, stoch)
Network communication using HTTP
What is an API
Reading the documentation and using an API
Mathematics for Market Trend analysis
Basics of Neural Networks
Using Neural Networks for Trading
Trade cryptocurrency on various crypto exchanges

Who Should Attend

Students curious about Finance and Market movements
Developers curious about applying Machine learning knowledge to finance

Target Audiences

Students curious about Finance and Market movements
Developers curious about applying Machine learning knowledge to finance

This course teaches the fundamentals of building a Trading Bot from scratchwhich will use Neural Networksto make a decision based on the training data which has been provided consisting of the historical price movements.

This course is divided into 4 modules

Network Communication Basics: This section deals with exploring the basics of HTTP requests. API interfaces are something which are dealt from the basics. Documentation reading of an API is also explained in good detail.

Building a Trading Bot from scratch: This section deals with the creation of a Trading Bot from scratch using Python 3. This bot will get the data from an exchange and then make decisions of buying or selling. These decisions will be made based on the nature of the candle graph. This will act as a very good example of a classical programming approach.

Market Indicators:This section deals with the basic market indicators like SMMA, Stoch, StochRSI and StopLoss. Trading strategies are also explained like bar-chart reversal along with the mathematics supporting them.

Neural Network: This section will act on the foundation established in the previous section where a basic trading bot framework called Gekko will be used as an intial working trading bot. A strategy which will use neural network will then be built on top of this trading bot. This section will also cover the basics of Neural Networks and act as a very good example of a Machine learning approach to solve problems

Future scope: This section will give suggestions on the future scope of this course. The extension of this course beyond Cryptocurrencies and many more such possibilities are discussed.

This course is created solely for educational purposes. Financial concepts mentioned in the course should not be considered as professional or financial advice. Any profit or loss incurred due to the deployment of the bot created in this course will completely be the responsibility of the User.

Hope you have fun exploring the depths of building a Trading Bot.

Happy Coding,

Vinay Phadnis 🙂

Course Curriculum

Chapter 1: Introduction

Lecture 1: What is a Trading Bot ?

Lecture 2: Use cases of a Trading Bot

Lecture 3: DISCLAIMER

Chapter 2: Network communication basics

Lecture 1: Basics of HTTP requests

Lecture 2: What is an API

Lecture 3: Documentation of API

Lecture 4: Parameters in a request

Lecture 5: Installing Postman

Lecture 6: Using Postman for making Requests

Chapter 3: Building a Trading Bot

Lecture 1: Program structure

Lecture 2: Initialising public and private keys

Lecture 3: Getting data from binance

Lecture 4: Signed request

Lecture 5: Basics of Logging

Lecture 6: Buying and Selling Orders

Lecture 7: Upscaling Candles

Chapter 4: Technical analysis of Stocks or Cryptocurrencies

Lecture 1: Simple Moving Average

Lecture 2: Exponential Moving Average

Lecture 3: Moving Average Convergence Divergence (MACD)

Chapter 5: Building a Neural Network

Lecture 1: The current problem

Lecture 2: What is Gekko

Lecture 3: Installing Gekko

Lecture 4: Strategy Boilerplate

Lecture 5: Functions in a strategy

Lecture 6: Initialize the Neural Network

Lecture 7: What are neurons

Lecture 8: What are weights

Lecture 9: What are Biases

Lecture 10: Activation functions

Chapter 6: Upgrading the Neural Network

Lecture 1: Training function

Lecture 2: What is SGDTrainer

Lecture 3: Normalizing inputs

Lecture 4: Predicting the candles

Lecture 5: What are Long and Short orders

Lecture 6: Calculating Loss values

Lecture 7: Update candles

Lecture 8: Stop Loss indicator

Lecture 9: Configuration file

Chapter 7: What next?

Lecture 1: Extending beyond Cryptocurrencies

Lecture 2: Using multi-nodal input network

Lecture 3: BONUS Lecture

Instructors

Vinay Phadnis
CTO, Machine Learning & Quantum Consultant

Rating Distribution

1 stars: 7 votes
2 stars: 8 votes
3 stars: 18 votes
4 stars: 24 votes
5 stars: 40 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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