Category Archives: Machine Learning

Route Planning with DynaQ Reinforcement Learning

Posted on April 23, 2024 by Pranab

The purpose of a simple route planning is to find the optimum route from one location to another that minimizes travel distance or time. Generally various heuristic optimization techniques are used to find optimum route. In this post we will … Continue reading →

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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 →

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Time Series Classification with Neural Network using Random Sub Sequence Statistics as Features

Posted on January 26, 2024 by Pranab

Deep Learning models generally extract features in the early layers of the network. It does away with the need for manual feature engineering making it attractive ML technique. However, this not always the case, time series clustering and classification being … Continue reading →

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Time Series Forecasting with Decomposition and Two Linear Networks

Posted on December 28, 2023 by Pranab

Many solutions for time series forecasting are available, starting from classic ARIMA to Deep Learning Transformer based. Results are varied. There doesn’t appear to be any consensus for the best performing forecasting model overall. In this post, we will go … Continue reading →

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Store Inventory Replenishment with Q Value Reinforcement Learning

Posted on August 25, 2023 by Pranab
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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 →

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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 →

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Realtime Concept Drift Detection for Machine Learning Classification Models

Posted on May 29, 2023 by Pranab

Concept drift can occur when the relationship between the input and output data changes i.e P(Y|X) changes while P(X) remains same. It happens when the behavior of the underlaying process has changed with respect to the model training time. This … Continue reading →

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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 →

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Synthetic Regression Data Generation in Python

Posted on January 22, 2023 by Pranab

In one of my projects, I needed to to generate synthetic data for a regression model. After looking around I could not find anything satisfactory, including Scikit-Learn. I wanted to have more control over the data generation process. I decided … Continue reading →

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