Nikita Shiledarbaxi

Guide To BenchmarkDotNet : A Benchmarking Library For DOTNET Developers

Table of contentsIntroductionWhat is a benchmark?Overview of BenchmarkDotNetFeatures supported by BenchmarkDotNetPros of BenchmarkDotNetConfig Components of benchmarking architecturePractical Implementation...

Guide To TAPAS (TAble PArSing) – A Technique To Retrieve Information From Tabular Data Using NLP

One of the most common forms of data that exists today is tabular data (structured data).In order to extract information from tabular data, you use Python libraries like Pandas or SQL-like languages. Google has recently...

Introduction To Infer.NET – A Framework For Probabilistic Programming in DOTNET

Table of contentsIntroductionProbabilistic ProgrammingBayesian InferenceOverview of Infer.NETHighlighting features of Infer.NETHow Infer.NET works?Practical implementationSteps for implementation in Visual...

Hands-on Python Guide to Style-based Age Manipulation (SAM) Technique

Table of contentsIntroductionWhat is age transformation?Overview of SAMWhy the name ‘style-based Age Manipulation’?Practical implementation of SAMPrerequisitesPre-trained modelDemo codeOutputGoogle colab notebooks...

Hands-On Python Guide To AllenAct – An Embodied AI Project

Table of contentsIntroductionCaptivating features of AllenActInstalling AllenActPractical implementationWhat is a Point Navigation task?What is an environment?Simulator usedAllenAct’s ‘Environment’Algorithm...

Semantic vs Instance vs Panoptic: Which Image Segmentation Technique To Choose

Image segmentation forms the basis of numerous Computer Vision projects. It segments the visual input in order to process it for tasks such as image classification and object detection. However, all the segmentation...

Guide to Panoptic Segmentation – A Semantic + Instance Segmentation Approach

Panoptic segmentation is an image segmentation method used for Computer Vision tasks. It unifies two distinct concepts used to segment images namely, semantic segmentation and instance segmentation. Panoptic...

Guide to SOLO and SOLOv2: Ways To Implement Instance Segmentation By Location

Table of contentsIntroductionCentral Idea of SOLOPractical implementation of SOLOPros of SOLOLimitations of SOLOOverview of SOLOv2Practical implementation of SOLOv2 Introduction SOLO (segment objects by locations) is a...

Hands-on Guide to AI Habitat: A Platform For Embodied AI Research

AI Habitat is a simulation platform developed with an intent to advance research in the domain of Embodied AI. It trains embodied agents (such as virtual robots and egocentric assistants) in highly photo-realistic 3D...

How To Supercharge Your Machine Learning Experiments with Comet.ml

Table of contentsIntroductionComet’s web-based UIWorkspacesProjectsExperimentsInstallation of comel_ml Python libraryPractical Implementation using KerasPractical implementation using PyTorch Introduction Comet.ml is...

Comprehensive Guide To Demand Forecasting Using ML.NET

Table of contentsProblem statementDataset usedAlgorithm usedPrerequisites for the implementation Data PreparationPath definitions and variable initializationData LoadingDefine time-series analysis pipelineModel...

Guide to Product Recommendation Using ML.NET

Table of contentsTwo types of recommendation systemsPrerequisites Algorithm usedDataset usedImplementation stepsPath definitions Context creationData loadingDefine the model training pipelineUse the model for...

Step-by-step Guide For Image Classification Using ML.NET

Table of contentsTransfer LearningImage Classification API of ML.NETDataset usedModel architecture usedPrerequisites for the implementationData PreparationCreating workspace directoryPath definitions and variable...

Introduction To ML.NET – An ML Framework For DOTNET Developers

ML.NET is an open-source Machine Learning framework developed by the .NET Foundation, an organization incorporated by the Microsoft Corporation. Basically, it is a robust library which .NET developers can use to...

How To Manage ML Experiments With neptune.ai

neptune.ai is a lightweight tool for experiment management and collaboration in Data Science projects. It is an organized place for all your experiments, data exploration Notebooks and more. It supports any kind of...

How To Use OpenBlender – The Leading Data Blending Tool

OpenBlender is an easy-to-handle means of enhancing the performance of Machine Learning models by augmenting them with external data from various open sources. It enables data-blending across multiple datasets which...

Guide To Flower – A Framework To Build Federated Learning Systems

As it is evident from the title itself, this article talks about an AI framework called Flower used for Federated Learning’s use cases. But before going into the details of the framework, let us have a quick...

Guide To MLflow – A Platform To Manage Machine Learning Lifecycle

MLflow is an open-source platform that enables smooth organization of a machine learning project. It handles the machine learning lifecycle such that if we use MLflow for deploying an ML project built on an unsupported...

Guide To Hummingbird – A Microsoft’s Library For Expediting Traditional Machine Learning Models

Conventional Machine Learning algorithms such as Linear Regression, Logistic Regression and Decision Tree are extensively used for a variety of real-world applications. For an easy-to-handle implementation of these...