Data Science


Practical Machine Learning: Real World Projects In Finance

We will work on real world data science and machine learning case studies of finance industry with python

3.40 (14 reviews)

Practical Machine Learning: Real World Projects In Finance


3.5 hours


Aug 2021

Last Update
Regular Price

What you will learn

Build Classification Models

Build Regression Models

Data Science Application in Finance Industry

Have a great intuition of many Machine Learning models

Make robust Machine Learning models

Know which Machine Learning model to choose for each type of problem


Machine learning in finance is now considered a key aspect of several financial services and applications, including managing assets, evaluating levels of risk, calculating credit scores, and even approving loans. Machine learning is a subset of data science that provides the ability to learn and improve from experience without being programmed.

As an application of artificial intelligence, machine learning focuses on developing systems that can access pools of data, and the system automatically adjusts its parameters to improve experiences. Computer systems run operations in the background and produce outcomes automatically according to how it is trained.

Machine learning tends to be more accurate in drawing insights and making predictions when large volumes of data are fed into the system. The financial services industry tends to encounter enormous volumes of data relating to daily transactions, bills, payments, vendors, and customers, which are perfect for machine learning.

Nowadays, many leading fintech and financial services companies are incorporating machine learning into their operations, resulting in a better-streamlined process, reduced risks, and better-optimized portfolios.

Machine learning is a branch of artificial intelligence that uses statistical models to make predictions.

In finance, machine learning algorithms are used to detect fraud, automate trading activities, and provide financial advisory services to investors.

Machine learning can analyze millions of data sets within a short time to improve the outcomes without being explicitly programmed.

  • Project-1 NYSE Stock Price Prediction

  • Project-2 RBI Resources Data Analysis

  • Project-3 E-signing of a loan based on financial history

  • Project-4 Prediction Of Default Of Credit Card

  • Project-5 Hybrid Mutual Fund Analysis


RBI Resources Data Analysis


Importing Data'


Model Building

Download the project files

NYSE Stock Price Prediction


Importing Data


Feature Engineering

Model Building

Download the project files


Marco29 August 2021

This is not a course you can follow without any problem, you have already to know how to set up a Jupyter Notebook, Install the libraries and use Python in general. Once you know this things you don't need the course cause then the actual coding is pretty basic and if you already know how to run everything why should you need to follow it?

Ikedinma19 April 2021

It is a great way to learn how to make projects and finally get on with the ideas that have been long pending in my notepad.


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