Thomas Bayes was an English statistician. As Stigler states, Thomas Bayes was born in 1701, with a probability value of 0.8! (link). Bayes' theorem has a useful application in machine learning. His papers were published by his friend, after his death. It is also said that his friend has used the theorem to prove existence of God.
Learning the Machine Learning, in a Human-friendly Way
Support Vector Machines (SVM) Explained with Visual Illustrations
Suppose there are two independent variables (features): x1 and x2. And there are two classes Class A and Class B. The following graphic shows the scatter diagram.
Logistic Regression: A Beginner's Visual Guide
Logistic regression is a supervised learning technique applied to classification problems.
In this post, let us explore:
In this post, let us explore:
- Logistic Regression model
- Advantages
- Disadvantages
- Example
- Hyperparemeters and Tuning
Building a Deep Learning Model using Keras
In this post, let us see how to build a deep learning model using Keras. If you haven't installed Tensorflow and Keras, I will show the simple way to install these two modules.
Mastering the Basics of Deep Learning with Illustrations
Deep learning is a powerful machine learning technique. These are widely used in
- Natural Language Processing (NLP)
- image/speech recognition
- robotics
- and many other artificial intelligence projects
ARIMA/SARIMA with Python: Understand with Real-life Example, Illustrations and Step-by-step Descriptions
Autoregressive Integrated Moving Average (ARIMA) is a popular time series forecasting model. It is used in forecasting time series variable such as price, sales, production, demand etc.
Subscribe to:
Posts (Atom)
Popular Posts
- ARIMA/SARIMA with Python: Understand with Real-life Example, Illustrations and Step-by-step Descriptions
- Demystifying Principal Component Analysis (PCA): A Beginner's Guide with Intuitive Examples & Illustrations
- Feature Selection: Filter method, Wrapper method and Embedded method
- Confusion Matrix, Accuracy, Precision, Recall, F score Explained with Intuitive Visual Examples
- Components of Time Series: A Beginner's Visual Guide
- Train-Test split and Cross-validation: Visual Illustrations & Examples
- Time series Cross-validation and Forecasting Accuracy: Understand with Illustrations & Examples
- Handling Missing Values in Python: Different Methods Explained with Visual Examples
- Scales of Measurement - Data types: Nominal, Ordinal, Interval and Ratio scale
- Support Vector Machines (SVM) Explained with Visual Illustrations