AI for Finance

AI for Finance, available at $34.99, has an average rating of 4.5, with 18 lectures, based on 66 reviews, and has 419 subscribers.

You will learn about Get hands-on financial forecasting experience using machine learning with Python, Keras, Scikit-Learn and pandas Use a variety of data preparation methods with financial data Predict future values based on single and multiple values Apply key modern Machine Learning methods for forecasting Understand the process behind choosing the best performing data preparation method and model Grasp Machine Learning forecasting on a specific real-world financial data This course is ideal for individuals who are This course is for aspiring data scientists, ML practitioners, as well as Investment Analysts and Portfolio managers working in the finance and investment industry. It is particularly useful for This course is for aspiring data scientists, ML practitioners, as well as Investment Analysts and Portfolio managers working in the finance and investment industry.

Enroll now: AI for Finance

Summary

Title: AI for Finance

Price: $34.99

Average Rating: 4.5

Number of Lectures: 18

Number of Published Lectures: 18

Number of Curriculum Items: 18

Number of Published Curriculum Objects: 18

Original Price: $109.99

Quality Status: approved

Status: Live

What You Will Learn

Get hands-on financial forecasting experience using machine learning with Python, Keras, Scikit-Learn and pandas

Use a variety of data preparation methods with financial data

Predict future values based on single and multiple values

Apply key modern Machine Learning methods for forecasting

Understand the process behind choosing the best performing data preparation method and model

Grasp Machine Learning forecasting on a specific real-world financial data

Who Should Attend

This course is for aspiring data scientists, ML practitioners, as well as Investment Analysts and Portfolio managers working in the finance and investment industry.

Target Audiences

This course is for aspiring data scientists, ML practitioners, as well as Investment Analysts and Portfolio managers working in the finance and investment industry.

A lot of solutions to key problems in the financial world require predicting the future patterns in data from the past to make better financial decisions right now. The evolution of modern machine learning methods and tools in recent years in the field of computer vision bring promise of the same progress in other important fields such as financial forecasting.

In this course, you’ll first learn how to quickly get started with ML in finances by predicting the future currency exchange rates using a simple modern machine learning method. In this example, you’ll learn how to choose the basic data preparation method and model and then how to improve them. In the next module, you’ll discover a variety of ways to prepare data and then see how they influence models training accuracy. In the last module, you’ll learn how to find and test a few key modern machine learning models to pick up the best performing one.

After finishing this course, you’ll have a solid introduction to apply ML methods to financial data forecasting.

About The Author

Jakub Konczyk has enjoyed and done programming professionally since 1995. He is a Python and Django expert and has been involved in building complex systems since 2006. He loves to simplify and teach programming subjects and share it with others. He first discovered Machine Learning when he was trying to predict the real estate prices in one of the early stage start-ups he was involved in. He failed miserably. Then he discovered a much more practical way to learn Machine Learning that he would like to share with you in this course. It boils down to “Keep it simple!” mantra.

Course Curriculum

Chapter 1: Introduction to Financial Forecasting

Lecture 1: The Course Overview

Lecture 2: What’s Financial Forecasting and Why It’s Important?

Lecture 3: Installing Pandas, Scikit-Learn, Keras, and TensorFlow

Lecture 4: Summary

Chapter 2: Predicting Currency Exchange Rates with Multi-Layer Perceptron

Lecture 1: Getting and Preparing the Currency Exchange Data

Lecture 2: Building the MLP Model with Keras

Lecture 3: Training and Testing the Model

Lecture 4: Summary and What’s Next?

Chapter 3: Loan Approval Prediction with GradientBoostingClassifier

Lecture 1: Getting and Preparing the Loan Approval Data

Lecture 2: Creating, Training, Testing, and Using a GradientBoostingClassfier Model

Lecture 3: Summary and What’s Next?

Chapter 4: Detecting Fraud in Financial Services Using Extreme GradientBoostingClassifier

Lecture 1: Getting and Preparing Financial Fraud Data

Lecture 2: Creating, Training, and Testing XGBoost Model

Lecture 3: Summary and What’s Next?

Chapter 5: Forecasting Stock Prices Using Long-Short Term Memory Network

Lecture 1: Getting and Preparing the Stock Prices Data

Lecture 2: Building the LSTM Model with Keras

Lecture 3: Training and Testing the Model

Lecture 4: Summary and What’s Next?

Instructors

Packt Publishing
Tech Knowledge in Motion

Rating Distribution

1 stars: 7 votes

2 stars: 3 votes

3 stars: 15 votes

4 stars: 18 votes

5 stars: 23 votes

Frequently Asked Questions

How long do I have access to the course materials?

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

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!