Author Archives: Nikita Shiledarbaxi - Page 8
Comet.ml is a Machine Learning experimentation platform which AI researchers and data scientists use to track, compare and explain their ML experiments. It allows ML practitioners to keep track of their databases, history of performed experiments, code modifications and production models. It enables model reproduction, easy maintenance of ML workflow and smooth collaboration throughout the…
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Time series forecasting in Machine Learning refers to a task of fitting the model to some historical data, analyzing the associated patterns and predicting future trends or observations. In the conventional statistical terms, the process of making such future predictions is called ‘extrapolation’ whilst modern domains refer to it as ‘forecasting’. In this article, we…
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Product recommendation in Machine Learning refers to the task of recommending product(s) to a customer based on his purchase history. A product recommender system is an ML model which suggests some items, content or services that a specific user would like to buy or indulge in. Here, we have used Amazon’s product co-purchasing network dataset…
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Product recommendation in Machine Learning refers to the task of recommending product(s) to a customer based on his purchase history. A product recommender system is an ML model which suggests some items, content or services that a specific user would like to buy or indulge in. Here, we have used Amazon’s product co-purchasing network dataset…
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Image classification is a Computer Vision task which falls into the category of Supervised Learning. We train a model to label an input image with one of the prescribed target classes based on the already labelled images of the training set. Here, we have a dataset having images of concrete surfaces. The task is to…
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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 implement Machine Learning projects coded in C# or F# language across several Microsoft products. When used with NimbusML, it also supports Python-coded models. The…
The post Introduction To ML.NET – An ML Framework For DOTNET Developers appeared first on Analytics India Magazine.
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 implement Machine Learning projects coded in C# or F# language across several Microsoft products. When used with NimbusML, it also supports Python-coded models. The…
The post Introduction To ML.NET – An ML Framework For DOTNET Developers appeared first on Analytics India Magazine.
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 project workflow. One can use it individually or in a team. Moreover, it can be utilized as a service or can be…
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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 overlap in time or location. Relevant variables from other datasets can be efficiently embedded in our data in a negligible amount of time using OpenBlender. …
The post How To Use OpenBlender – The Leading Data Blending Tool appeared first on Analytics India Magazine.
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 introduction of the Federated Learning approach itself. What is Federated Learning ? Conventional Machine Learning models require the…
The post Guide To Flower – A Framework To Build Federated Learning Systems appeared first on Analytics India Magazine.