Machine Learning

Learn basics to advanced concepts in machine learning and its implementation in financial markets. Includes deep learning, tensor flows, installation guides, downloadable strategy codes along with real-market data.

Top Picks

Neural Network In Python: Types, Structure And Trading Strategies

What is a neural network and how does it work? How can you create a neural network with the famous Python programming language? In this tutorial, learn the concept of neural networks, their work, and their applications along with Python in trading....
19 min read

Machine Learning Basics: Components, Application, Resources and More

Machine Learning basics, algorithms, concepts and techniques are the talk of the day! Machine Learning has dramatically altered every field. Dive into the basics of machine learning, and learn all about it....
13 min read

An Introduction to Unsupervised Learning for Trading

Learn about the basics of unsupervised learning algorithms and their use cases in Finance/Investment/Trading with examples in Python....
15 min read

Gold Price Prediction: Step By Step Guide Using Python Machine Learning

A guide about Gold price using prediction using machine learning in Python. Learn about defining the variables to create a linear regression model, and eventually predicting the Gold ETF prices....
5 min read

Machine Learning Strategy using Blueshift Visual Programming

We use Blueshift Visual Programming to create a machine learning strategy without writing any code! We also backtest and then live trade the strategy....
10 min read

Reinforcement Learning in Trading: Components, Challenges, and More

In this article, we will start with the concept of reinforcement learning and its components. Further, we will look at the learning process of the model and how to apply in trading....
12 min read

Introduction to Support Vector Machines

In this article, we will understand how support vector machines work and its application in trading. We will also go through the maths behind the SVM and the process of using it in a non-linear model....
15 min read

Decision Tree For Trading Using Python

We will focus on trading and how to use decision trees to find trading rules that allow us to gain an edge in the market....
14 min read

Machine Learning

Machine Learning Strategy using Blueshift Visual Programming

We use Blueshift Visual Programming to create a machine learning strategy without writing any code! We also backtest and then live trade the strategy....
10 min read

Reinforcement Learning in Trading: Components, Challenges, and More

In this article, we will start with the concept of reinforcement learning and its components. Further, we will look at the learning process of the model and how to apply in trading....
12 min read

Cross Validation in Finance: Purging, Embargoing, Combination

In this blog, we will understand the concept of embargoing and purging and its application in cross validation of financial data...
9 min read

Forward Propagation In Neural Networks: Components and Applications

Forward propagation in Neural networks implies that data flows in the forward direction, from the input layer to the output layer with a hidden layer in between which processes the input variables and gives us an output....
12 min read

Artificial Intelligence & Machine Learning in Trading

Use AI & machine learning in trading. Impact of artificial intelligence & machine learning on trading. Implementations & applications of AI & ML....
9 min read

Deep Learning in Finance

Learn all about Deep Learning, Models, Applications in finance and Future. Get a general overview of Deep Learning and its use in finance....
13 min read

Building and Regularizing Linear Regression Models in Scikit-learn

Linear regression models, regularization, its examples (Ridge, Lasso and Elastic Net regularizations) and how they can be implemented in Python using the scikit learn library - are all covered in this blog....
13 min read

Introduction to XGBoost in Python

XGBoost is a gradient boosting model which reduces computation time and consumes fewer resources. Python code to predict long-short on US stocks is also covered...
15 min read

Principal Component Analysis in Trading

We will try to understand the principal component analysis and its application in trading. We also understand Eigenvalues and Eigenvectors along with covariance, which is used in Principal Component Analysis....
12 min read

Introduction to Support Vector Machines

In this article, we will understand how support vector machines work and its application in trading. We will also go through the maths behind the SVM and the process of using it in a non-linear model....
15 min read