Category Archives: Data Science

Time Series Feature Engineering with Histogram

Posted on March 30, 2024 by Pranab

Typically time series data requires manual feature engineering unless you are using Deep Learning. Deep Learning alleviates you from this task but there is no guarantee. There are many techniques for feature engineering time series. In this post will use … Continue reading →

Posted in AI, Anomaly Detection, Data Science, feature engineering, Machine Learning, Time Series Analytic | Tagged , , , , , , | Leave a comment

Time Series Data Exploration with Wavelet Transform

Posted on September 29, 2023 by Pranab

Time series data provides time domain information and Fast Fourier Transform provides frequency domain information only. What if you wanted both, for example you may be interested in frequency domain information only within a specified time range. Wavelet transform provides … Continue reading →

Posted in Anomaly Detection, Data Science, Python, Time Series Analytic | Tagged | Leave a comment

Online Advertisement Placement with Contextual Bandit.

Posted on July 27, 2023 by Pranab

There is a class of algorithms called Multi Arm Bandit (MAB) applicable for Reinforcement Leaning problems without state. Sometimes there is side information available for each action. MAB algorithms that take this side information aka context into account are called … Continue reading →

Posted in AI, Data Science, Machine Learning, Python, Reinforcement Learning | Tagged , | Leave a comment

Time Series Sequence Anomaly Detection with Markov Chain

Posted on June 28, 2023 by Pranab

There are many algorithms for anomaly detection in time series including Deep Learning based solutions. The anomalies are of 2 types, point and sequence. Sequence anomaly detection is generally of more interest for time series data. In this post we … Continue reading →

Posted in Anomaly Detection, Data Science, Machine Learning, Python, Statistics, time series | Tagged , | Leave a comment

Synthetic Time Series Data Generation

Posted on March 29, 2023 by Pranab

Recently I started working on a Python package which is everything time series, with specific focus on EDA, forecasting, classification and anomaly detection. It will leverage other Python libraries wherever appropriate. My first realization was that I need a Python … Continue reading →

Posted in Data Science, Python, time series | Tagged , | 3 Comments

Simulating A/B Test with Counterfactual and Machine Learning Regression Model

Posted on February 28, 2023 by Pranab

Performing A/B test is costly. It takes time and resource.AB testing is a way trying multiple versions of something to find out which works best based on some metric. it’s also called Randomized Controlled Test (RCT). There are many application … Continue reading →

Posted in AI, causality, Data Science, Deep Learning, Machine Learning, Python | Tagged , , , | Leave a comment

Stock Portfolio Balancing with Monte Carlo Simulation

Posted on August 23, 2022 by Pranab

Portfolio balancing is a complex optimization problem. The problem can be stated as assignment of weights to different stocks in the portfolio so that a metric called Sharpe Ratio is maximized. In this post we will see how Monte Carlo … Continue reading →

Posted in Data Science, Python, Simulation, Statistics | Tagged , , | 1 Comment

Tabular Data Column Semantic Type Identification with Contrastive Deep Learning

Posted on June 30, 2022 by Pranab

When data is aggregated from various source in a dynamic environment where the data format might change without any notice, identifying semantic type of columns in data is a challenging problem. In this post the problem semantic type identification of … Continue reading →

Posted in Data Science, Deep Learning, Python, PyTorch | Tagged , | 1 Comment

Feature Selection with Information Theory Based Techniques in Python.

Posted on May 29, 2022 by Pranab

Feature selection is the process of selection a subset of features most relevant from a given set of features for a supervised machine learning problem. There are many techniques for feature selection. in this post we will use 4 information … Continue reading →

Posted in Data Science, Machine Learning, Python | Tagged , | 1 Comment

Remedial Action Recommendation with Machine Learning and Genetic Algorithm

Posted on January 26, 2022 by Pranab

Prescriptive analytic sits at the top of a three tier analytic pyramid. The bottom layers are descriptive and predictive analytic. Prescriptive analytic entails action recommendations based on the results of descriptive and predictive analytic, which if executed will have have … Continue reading →

Posted in AI, Data Science, Deep Learning, Machine Learning, Optimizatiom, Python, PyTorch | Tagged , , | Leave a comment