Analytics Vidhya

FEBRUARY 20, 2025

If you’re working with AI/ML workloads(like me) and trying to figure out which data format to choose, this post is for you.

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Analytics Vidhya

APRIL 5, 2024

This article is […] The post Top 40 Python Libraries for AI, ML and Data Science appeared first on Analytics Vidhya. A massive community with libraries for machine learning, sleek app development, data analysis, cybersecurity, and more. This flexible language has you covered for all things AI and beyond.

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KDnuggets

OCTOBER 12, 2023

It delves into several software engineering techniques and patterns applied to ML. This article talks about several best practices for writing ETLs for building training datasets.

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Analytics Vidhya

MARCH 13, 2024

Introduction Whether you’re a fresher or an experienced professional in the Data industry, did you know that ML models can experience up to a 20% performance drop in their first year? ML Monitoring aids in early […] The post Complete Guide to Effortless ML Monitoring with Evidently.ai

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Analytics Vidhya

MARCH 28, 2024

Machine learning (ML) can seem complex, but what if you could train a model without writing any code? This guide unlocks the power of ML for everyone by demonstrating how to train a ML model with no code.

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KDnuggets

OCTOBER 8, 2024

Learn how Docker can keep your ML models running smoothly, every time. Tired of fixing the same deployment issues?

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Analytics Vidhya

MAY 6, 2024

Introduction Machine learning (ML) has become a game-changer across industries, but its complexity can be intimidating. Why […] The post How to Build a ML Model in 1 Minute using ChatGPT appeared first on Analytics Vidhya. This article explores how to use ChatGPT to build machine learning models.

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Machine Learning Mastery

AUGUST 13, 2024

So getting started in the ML field wouldn’t be any different. This is why today I want to highlight some of the essential tools that every beginner — or person willing to get started — with ML should be using. We have all experienced it: starting is the toughest part of any journey.

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Flipboard

NOVEMBER 22, 2024

This post is part of an ongoing series about governing the machine learning (ML) lifecycle at scale. The data mesh architecture aims to increase the return on investments in data teams, processes, and technology, ultimately driving business value through innovative analytics and ML projects across the enterprise.

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KDnuggets

SEPTEMBER 20, 2023

On October 11th, 2023 the Feature Store Summit will bring together leading ML companies, such as Uber, WeChat and more, for in-depth discussions about data and AI.

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KDnuggets

JANUARY 3, 2024

This article will provided you with a better understanding of what skills are required for a junior ML developer to be considered for a job. If you are looking to land your first job, you should read this article thoroughly.

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Analytics Vidhya

FEBRUARY 6, 2024

It caters to various ML needs, including a powerful focus on Generative AI, which allows you to harness the power of large language models (LLMs) for: Importance of GCP Vertex AI in Generative AI […] The post Build, Deploy, and Manage ML Models with Google Vertex AI appeared first on Analytics Vidhya.

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Analytics Vidhya

FEBRUARY 6, 2024

In this blog, we’ll look into the top 5 WhatsApp […] The post 5 WhatsApp Groups for Data Science and ML Enthusiasts appeared first on Analytics Vidhya. WhatsApp, the ubiquitous messaging platform, has emerged as an unexpected yet potent medium for knowledge sharing and networking.

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Machine Learning Mastery

NOVEMBER 22, 2024

This well-known motto perfectly captures the essence of ensemble methods: one of the most powerful machine learning (ML) approaches -with permission from deep neural networks- to effectively address complex problems predicated on complex data, by combining multiple models for addressing one predictive task. Unity makes strength.

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Analytics Vidhya

APRIL 11, 2024

These tools enhance the efficiency […] The post Here are 9 Must Need Machine Learning Tools for Your ML Project appeared first on Analytics Vidhya. Many tools and libraries have emerged as machine learning applications expand to help developers build and deploy machine learning models.

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Towards AI

DECEMBER 26, 2024

4 Things to Keep in Mind Before Deploying Your ML Models This member-only story is on us. medium.com Regardless of the project, it might be software development or ML Model building. Last Updated on December 26, 2024 by Editorial Team Author(s): Richard Warepam Originally published on Towards AI. Upgrade to access all of Medium.

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AWS Machine Learning Blog

DECEMBER 9, 2024

With access to a wide range of generative AI foundation models (FM) and the ability to build and train their own machine learning (ML) models in Amazon SageMaker , users want a seamless and secure way to experiment with and select the models that deliver the most value for their business.

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AWS Machine Learning Blog

NOVEMBER 19, 2024

At the time, I knew little about AI or machine learning (ML). But AWS DeepRacer instantly captured my interest with its promise that even inexperienced developers could get involved in AI and ML. Panic set in as we realized we would be competing on stage in front of thousands of people while knowing little about ML.

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insideBIGDATA

NOVEMBER 9, 2023

Our friends over at Sama recently published a comprehensive report on the potential and challenges of AI as reported by Machine Learning professionals.

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KDnuggets

SEPTEMBER 5, 2024

A beginner tutorial on building a simple web application for machine learning model inference using FastAPI and Jinja2 templates.

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KDnuggets

APRIL 30, 2024

Want to build and deploy robust machine learning systems to production? Start learning MLOps today with these courses from Google.

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AWS Machine Learning Blog

DECEMBER 12, 2024

The new SDK is designed with a tiered user experience in mind, where the new lower-level SDK ( SageMaker Core ) provides access to full breadth of SageMaker features and configurations, allowing for greater flexibility and control for ML engineers. In the following example, we show how to fine-tune the latest Meta Llama 3.1

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Towards AI

DECEMBER 15, 2024

Last Updated on December 15, 2024 by Editorial Team Author(s): Raghu Teja Manchala Originally published on Towards AI. Short and Concise: The Most Asked Regression Metrics in Interviews. Source: Image by Sam Nguyen on Avada Over the past few years, I have had numerous interviews, ranging from scenario-based to technical rounds.

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Analytics Vidhya

FEBRUARY 1, 2023

Introduction Artificial Intelligence (AI) and Machine Learning (ML) have rapidly become some of the most important technologies in the field of cybersecurity. With the increasing amount of data and sophisticated cyber threats, AI and ML are being used to strengthen the security of organizations and individuals.

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insideBIGDATA

APRIL 22, 2023

The company surveyed more than 1,600 executives and ML practitioners to uncover what’s working, what’s not, and the best practices for organizations to deploy AI for real business impact. Our friends over at Scale are excited to introduce the 2nd edition of Scale Zeitgeist: AI Readiness Report!

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insideBIGDATA

FEBRUARY 23, 2023

It’s a wonderful learning resource for tree-based techniques in statistical learning, one that’s become my go-to text when I find the need to do a deep dive into various ML topic areas for my work. The methods […]

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Flipboard

MARCH 16, 2025

AI was certainly getting better at predictive analytics and many machine learning (ML) algorithms were being used for voice recognition, spam detection, spell ch… Read More What seemed like science fiction just a few years ago is now an undeniable reality. Back in 2017, my firm launched an AI Center of Excellence.

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KDnuggets

OCTOBER 6, 2023

Elevate Your Search Engine Skills! Join Uplimit's SearchML Course now for a 4-week deep dive into machine learning and search. Boost rankings, enhance retrieval, and build with OpenSearch. Enroll today and level up with expert guidance!

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Analytics Vidhya

MAY 17, 2024

Introduction Do you know, that you can automate machine learning (ML) deployments and workflow? This can be done using Machine Learning Operations (MLOps), which are a set of rules and practices that simplify and automate ML deployments and workflows. Yes, you heard it right.

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KDnuggets

AUGUST 15, 2024

The AI and ML complexity results in a growing number and diversity of jobs that require AI & ML expertise. We’ll give you a rundown of these jobs regarding the technical skills they need and the tools they employ.

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Flipboard

NOVEMBER 14, 2024

Machine learning (ML) models contain numerous adjustable settings called hyperparameters that control how they learn from data. Unlike model parameters that are learned automatically during training, hyperparameters must be carefully configured by developers to optimize model performance.

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insideBIGDATA

MARCH 18, 2024

Today at NVIDIA GTC, Hewlett Packard Enterprise (NYSE: HPE) announced updates to one of the industry’s most comprehensive AI-native portfolios to advance the operationalization of generative AI (GenAI), deep learning, and machine learning (ML) applications.

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insideBIGDATA

DECEMBER 30, 2023

They bring human experts into the loop to view how the ML performed on a set of data. Scientists at the Department of Energy’s Pacific Northwest National Laboratory have put forth a new way to evaluate an AI system’s recommendations.

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KDnuggets

OCTOBER 16, 2024

Where can you find projects dealing with advanced ML topics? GitHub is a perfect source with its many repositories. I’ve selected ten to talk about in this article.

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Analytics Vidhya

JUNE 14, 2024

Introduction Efficient ML models and frameworks for building or even deploying are the need of the hour after the advent of Machine Learning (ML) and Artificial Intelligence (AI) in various sectors. Although there are several frameworks, PyTorch and TensorFlow emerge as the most famous and commonly used ones.

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Machine Learning Mastery

AUGUST 26, 2024

As we progress through 2024, machine learning (ML) continues to evolve at a rapid pace. Python, with its rich ecosystem of libraries, remains at the forefront of ML development.

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