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Getting Started with Scikit-learn in 5 Steps

KDnuggets

This tutorial offers a comprehensive hands-on walkthrough of machine learning with Scikit-learn. Readers will learn key concepts and techniques including data preprocessing, model training and evaluation, hyperparameter tuning, and compiling ensemble models for enhanced performance.

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Free GPUs for Everyone! Get Started with Google Colab for Machine Learning and Deep Learning

Analytics Vidhya

Google Colab – Now Build Large Deep Learning Models on your Machine! Get Started with Google Colab for Machine Learning and Deep Learning appeared first on Analytics Vidhya. “Memory Error” – that all too familiar dreaded message in Jupyter notebooks. The post Free GPUs for Everyone!

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Getting Started with Scikit-learn for Classification in Machine Learning

KDnuggets

The tutorial will introduce you to the scikit-learn module and its various features. It will also give you a brief overview of the multiclass classification problem through various algorithms.

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Getting started with Deep Learning? Here’s a quick guide explaining everything at a place!

Analytics Vidhya

The post Getting started with Deep Learning? ArticleVideo Book This article was published as a part of the Data Science Blogathon. In this blog, I’ll provide a brief rundown of. Here’s a quick guide explaining everything at a place! appeared first on Analytics Vidhya.

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The Definitive Entity Resolution Buyer’s Guide

You’ll learn about use cases, technology and deployment options, top ten evaluation criteria and more. Whether you're an entity resolution veteran or just getting started, you’re guaranteed to learn something new from this comprehensive guide. This guide provides many valuable insights. Download it today.

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Spatial Intelligence: Why GIS Practitioners Should Embrace Machine Learning- How to Get Started.

Towards AI

You just want to create and analyze simple maps not to learn algebra all over again. How GIS and Machine Learning Works According to Geography Publishing, In GIS, machine learning is like providing a cartographer with the strongest magnifying glass on the planet. Types of Machine Learning for GIS 1.

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Getting Started with Machine Learning?—?Implementing Linear Regression from Scratch

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Using the machine learning models in your projects is quite. The post Getting Started with Machine Learning?—?Implementing Implementing Linear Regression from Scratch appeared first on Analytics Vidhya.

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How to Package and Price Embedded Analytics

Just by embedding analytics, application owners can charge 24% more for their product. How much value could you add? This framework explains how application enhancements can extend your product offerings. Brought to you by Logi Analytics.

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New Study: 2018 State of Embedded Analytics Report

Why do some embedded analytics projects succeed while others fail? We surveyed 500+ application teams embedding analytics to find out which analytics features actually move the needle. Read the 6th annual State of Embedded Analytics Report to discover new best practices. Brought to you by Logi Analytics.

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Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes. Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics.

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5 Early Indicators Your Embedded Analytics Will Fail

Many application teams leave embedded analytics to languish until something—an unhappy customer, plummeting revenue, a spike in customer churn—demands change. But by then, it may be too late. In this White Paper, Logi Analytics has identified 5 tell-tale signs your project is moving from “nice to have” to “needed yesterday.".

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The Definitive Guide to Predictive Analytics

The Definitive Guide to Predictive Analytics has everything you need to get started, including real-world examples, steps to build your models, and solutions to common data challenges. What You'll Learn: 7 steps to embed predictive analytics in your application—from identifying a problem to solve to building your prototype.