Working with MySQL Database using Python As a data scientist, one should be able to acquire or convert the raw data into actionable information. Once the data is organized,
An RNN (Recurrent Neural Network) model to predict stock price. Predicting Stock Price of a company is one of the difficult task in Machine Learning/Artificial Intelligence. This is difficult
Finding Outliers in Machine Learning Did you ever notice? Anything that stands away from the “common” will always demand attention. Such un-common observation is usually called as outlier. As
Introduction to Data Visualization Bar Chart: A bar chart or bar graph is a chart or graph that presents categorical data with rectangular bars with heights or lengths proportional
Topic Modeling – Latent Semantic Analysis (LSA) and Singular Value Decomposition (SVD): Singular Value Decomposition is a Linear Algebraic concept used in may areas such as machine learning (principal
A Machine Learning or Deep Learning model must be in balanced state (Generalized) If you ever built a supervised Machine Learning model on some real-time data, it is impossible
“Activation Functions” play a critical role in the architecture of Artificial Neural Networks (ANN). The Deep neural networks are being successfully used in many emerging domains to solve real
Feature Engineering for Structured Data (numerical and categorical) “Best Ingredients make Best Dish “, the same way “Best Features make Best Model” As part of any Machine Learning project,
Regression – Find relation between Multiple Inputs and Target variable One Input variable : When only one input variable and one output variable, scatter chart is useful in finding
Step-by-Step Data Science Project (End to End Regression Model) We took “Melbourne housing market dataset from kaggle” and built a model to predict house price. While building the model