Search results for public cloud

Found 431 documents, 5930 searched:

• Getting Started with Google Cloud Platform in 5 Steps

  Explore the essentials of Google Cloud Platform for data science and ML, from account setup to model deployment, with hands-on project examples.

  https://www.kdnuggets.com/5-steps-google-cloud-platform

• Top 7 Free Cloud Notebooks for Data Science

  Cloud notebooks are game-changers for data science, providing free access to computing, pre-built environments, collaboration features, and third-party integrations - everything you need to enhance your workflow.

  https://www.kdnuggets.com/top-7-free-cloud-notebooks-for-data-science

• How Cloud Computing Enhances Data Science Workflows

  Cloud computing offers the efficiency, scalability, and security data science workflows need. Discover how it provides these benefits here.

  https://www.kdnuggets.com/2023/08/cloud-computing-enhances-data-science-workflows.html

• 11 Best Practices of Cloud and Data Migration to AWS Cloud

  list of Best Practices compiled from our learnings during our migration journey to the AWS cloud.

  https://www.kdnuggets.com/2023/04/11-best-practices-cloud-data-migration-aws-cloud.html

• Beginner’s Guide to Cloud Computing

  Learn how cloud computing works, different types of models, top cloud platforms, and applications.

  https://www.kdnuggets.com/2023/01/beginner-guide-cloud-computing.html

• Publications on Data Science, Machine Learning, AI & Analytics

    Featured Publications The Machine Learning Mastery EBook Catalog Machine Learning Mastery Frustrated with one-off articles and too much math? Take the Next Step and Read more »

  https://www.kdnuggets.com/publication/index.html

• Top 5 Free Cloud Notebooks in 2022

  Create and collaborate on data science projects or train machine learning models using free cloud Jupyter notebook platforms. You get a hassle-free IDE experience and free compute resources.

  https://www.kdnuggets.com/2022/04/top-5-free-cloud-notebooks-2022.html

• Cloud ML In Perspective: Surprises of 2021, Projections for 2022

  Let’s take a closer look on Cloud ML market in 2021 in retrospective (with occasional drills into realities of 2020, too). Read this in-depth analysis.

  https://www.kdnuggets.com/2021/12/cloud-ml-perspective-surprises-2021-projections-2022.html

• Build a Serverless News Data Pipeline using ML on AWS Cloud

  This is the guide on how to build a serverless data pipeline on AWS with a Machine Learning model deployed as a Sagemaker endpoint.

  https://www.kdnuggets.com/2021/11/build-serverless-news-data-pipeline-ml-aws-cloud.html

• Deploy a Dockerized FastAPI App to Google Cloud Platform

  A short guide to deploying a Dockerized Python app to Google Cloud Platform using Cloud Run and a SQL instance.

  https://www.kdnuggets.com/2021/05/deploy-dockerized-fastapi-app-google-cloud-platform.html

• ETL in the Cloud: Transforming Big Data Analytics with Data Warehouse Automation

  Today, organizations are increasingly implementing cloud ETL tools to handle large data sets. With data sets becoming larger by the day, unified ETL tools have become crucial for data integration needs of enterprises.

  https://www.kdnuggets.com/2021/04/etl-cloud-transforming-big-data-analytics-data-warehouse-automation.html

• Deploy a Machine Learning Pipeline to the Cloud Using a Docker Container

  In this tutorial, we will use a previously-built machine learning pipeline and Flask app to demonstrate how to deploy a machine learning pipeline as a web app using the Microsoft Azure Web App Service.

  https://www.kdnuggets.com/2020/06/deploy-machine-learning-pipeline-cloud-docker.html

• Serverless Machine Learning with R on Cloud Run

  Expedite the deployment of your machine models using serverless cloud infrastructure. In this tutorial, we explore creating and deploying a model which scraps real time Twitter data and returns interactive visualization using R.

  https://www.kdnuggets.com/2020/02/serverless-machine-learning-r-cloud-run.html

• Alternative Cloud Hosted Data Science Environments

  Over the years new alternative providers have risen to provided a solitary data science environment hosted on the cloud for data scientist to analyze, host and share their work.

  https://www.kdnuggets.com/2019/12/alternative-cloud-data-science-environments.html

• Best Deals in Deep Learning Cloud Providers: From CPU to GPU to TPU

  A detailed comparison of the best places to train your deep learning model for the lowest cost and hassle, including AWS, Google, Paperspace, vast.ai, and more.

  https://www.kdnuggets.com/2018/11/deep-learning-cloud-providers-cpu-gpu-tpu.html

• The Internet of Things in the Cloud

  Cloud computing is the next evolutionary step in Internet-based computing, which provides the means for delivering ICT resources as a service. Internet-of-Things can benefit from the scalability, performance and pay-as-you-go nature of cloud computing infrastructures.

  https://www.kdnuggets.com/2017/05/internet-of-things-iot-cloud.html

• Why the Data Scientist and Data Engineer Need to Understand Virtualization in the Cloud

  This article covers the value of understanding the virtualization constructs for the data scientist and data engineer as they deploy their analysis onto all kinds of cloud platforms. Virtualization is a key enabling layer of software for these data workers to be aware of and to achieve optimal results from.

  https://www.kdnuggets.com/2017/01/data-scientist-engineer-understand-virtualization-cloud.html

• Cloud Computing Key Terms, Explained

  A concise overview of 20 core cloud computing ecosystem concepts. The focus here is on the terminology, not The Big Picture.

  https://www.kdnuggets.com/2016/06/cloud-computing-key-terms-explained.html

• Hadoop as a Service: 18 Cloud Options

  Hadoop as a service in the cloud makes big data applications and projects easier to approach and these 18 platforms each provide their own unique solutions.

  https://www.kdnuggets.com/2015/04/hadoop-as-service-18-cloud-options.html

• Google BigQuery Public Datasets

  Google BigQuery is not only a fantastic tool to analyze data, but it also has a repository of public data, including GDELT world events database, NYC Taxi rides, GitHub archive, Reddit top posts, and more.

  https://www.kdnuggets.com/2015/02/google-bigquery-public-datasets.html

• Interview: Eli Collins, Cloudera on Evolution and Future of Big Data Ecosystem

  We discuss the change in Big Data priorities, risks, Big Data ecosystem, rise of data culture in organizations, challenges, advice and more.

  https://www.kdnuggets.com/2015/02/interview-eli-collins-cloudera-big-data-ecosystem.html

• 2014 Jan Publications: Analytics, Big Data, Data Mining and Data Science

  All (69) | News, Software (19) | Courses, Events (20) | Publications (15) Top KDnuggets tweets, Jan 17-19: Learning from Data: Caltech free online course; Read more »

  https://www.kdnuggets.com/2014/01/publications-old.html

• 2013 Dec Publications: Analytics, Big Data, Data Mining and Data Science

  All (95) | News, Software (27) | Courses, Events (12) | Jobs | Academic | Publications (38) Unicorn Data Scientists vs Data Science Teams - Read more »

  https://www.kdnuggets.com/2013/12/publications.html

• Data: Government, State, City, Local and Public

  This is a directory of government, federal, state, city, local and other public datasets. See also Data APIs, Hubs, Marketplaces, Platforms, Portals, and Search Engines. Read more »

  https://www.kdnuggets.com/datasets/government-local-public.html

• 2013 Nov Publications: Analytics, Big Data, Data Mining and Data Science

  All (116) | News, Software (28) | Courses, Events (23) | Jobs | Academic | Publications (36) LIONbook Chapter 15: Dimensionality reduction - Nov 28, Read more »

  https://www.kdnuggets.com/2013/11/publications.html

• Cloud Analytics and SaaS Providers

  Algorithms.io, offering API to embed popular machine learning algorithms into applications; R as a service. Alpine Data Labs, helps you uncover the predictive analytic power Read more »

  https://www.kdnuggets.com/companies/cloud-analytics-saas.html

• Best Practices for Building ETLs for ML

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

  https://www.kdnuggets.com/best-practices-for-building-etls-for-ml

• How to Build a Streaming Semi-structured Analytics Platform on Snowflake

  Building a datalake for semi-structured data or json has always been challenging. Imagine if the json documents are streaming or continuously flowing from healthcare vendors then we need a robust modern architecture that can deal with such a high volume. At the same time analytics layer also needs to be created so as to generate value from it.

  https://www.kdnuggets.com/2023/07/build-streaming-semistructured-analytics-platform-snowflake.html

• Scaling Data Management Through Apache Gobblin

  Software companies can manage big data at a hyper-scale on different infrastructure stacks using Apache Gobblin.

  https://www.kdnuggets.com/2023/01/scaling-data-management-apache-gobblin.html

• Machine Learning on the Edge

  Edge ML involves putting ML models on consumer devices where they can independently run inferences without an internet connection, in real-time, and at no cost.

  https://www.kdnuggets.com/2022/10/machine-learning-edge.html

• 5 Key Components of a Data Sharing Platform

  Read this article for an overview of what the components of a data-sharing platform are.

  https://www.kdnuggets.com/2022/05/5-key-components-data-sharing-platform.html

• Data Warehousing with Snowflake for Beginners

  This tutorial provides only a brief synopsis of the data warehouse in Snowflake, which we will go through in more detail.

  https://www.kdnuggets.com/2022/02/data-warehousing-snowflake-beginners.html

• A Full End-to-End Deployment of a Machine Learning Algorithm into a Live Production Environment

  How to use scikit-learn, pickle, Flask, Microsoft Azure and ipywidgets to fully deploy a Python machine learning algorithm into a live, production environment.

  https://www.kdnuggets.com/2021/12/deployment-machine-learning-algorithm-live-production-environment.html

• 11 Best Companies to Work for as a Data Scientist

  This list of best data science companies aims to go beyond the usual and expected. Some great and perhaps underrated options to get a job as a data scientist.

  https://www.kdnuggets.com/2021/12/11-best-companies-work-data-scientist.html

• 10 Key AI & Data Analytics Trends for 2022 and Beyond

  What AI and data analytics trends are taking the industry by storm this year? This comprehensive review highlights upcoming directions in AI to carefully watch and consider implementing in your personal work or organization.

  https://www.kdnuggets.com/2021/12/10-key-ai-trends-for-2022.html

• Machine Learning Model Development and Model Operations: Principles and Practices">Machine Learning Model Development and Model Operations: Principles and Practices

  The ML model management and the delivery of highly performing model is as important as the initial build of the model by choosing right dataset. The concepts around model retraining, model versioning, model deployment and model monitoring are the basis for machine learning operations (MLOps) that helps the data science teams deliver highly performing models.

  https://www.kdnuggets.com/2021/10/machine-learning-model-development-operations-principles-practice.html

• Overview of MLOps

  Building a machine learning model is great, but to provide real business value, it must be made useful and maintained to remain useful over time. Machine Learning Operations (MLOps), overviewed here, is a rapidly growing space that encompasses everything required to deploy a machine learning model into production, and is a crucial aspect to delivering this sought after value.

  https://www.kdnuggets.com/2021/03/overview-mlops.html

• MLOps – “Why is it required?” and “What it is”?

  Creating an model that works well is only a small aspect of delivering real machine learning solutions. Learn about the motivation behind MLOps, the framework and its components that will help you get your ML model into production, and its relation to DevOps from the world of traditional software development.

  https://www.kdnuggets.com/2020/12/mlops-why-required-what-is.html

• Industry 2021 Predictions for AI, Analytics, Data Science, Machine Learning

  We bring you industry predictions from 12 innovative companies - what key trends they expect in 2021 in AI, Analytics, Data Science, and Machine Learning?

  https://www.kdnuggets.com/2020/12/industry-2021-predictions-ai-data-science-machine-learning.html

• AI and Automation meets BI">AI and Automation meets BI

  Organizations use a variety of BI tools to analyze structured data. These tools are used for ad-hoc analysis, and for dashboards and reports that are essential for decision making. In this post, we describe a new set of BI tools that continue this trend.

  https://www.kdnuggets.com/2020/11/ai-automation-meets-bi.html

• A Tour of End-to-End Machine Learning Platforms

  An end-to-end machine learning platform needs a holistic approach. If you’re interested in learning more about a few well-known ML platforms, you’ve come to the right place!

  https://www.kdnuggets.com/2020/07/tour-end-to-end-machine-learning-platforms.html

• Everything a Data Scientist Should Know About Data Management">Everything a Data Scientist Should Know About Data Management

  For full-stack data science mastery, you must understand data management along with all the bells and whistles of machine learning. This high-level overview is a road map for the history and current state of the expansive options for data storage and infrastructure solutions.

  https://www.kdnuggets.com/2019/10/data-scientist-data-management.html

• The Economics and Benefits of Artificial Intelligence

  In this article, focus on current AI, which is mostly based on the algorithms that can do predictions, and discuss how the economics of AI works and how it may affect business.

  https://www.kdnuggets.com/2018/09/economics-benefits-artificial-intelligence.html

• Presto for Data Scientists – SQL on anything

  Presto enables data scientists to run interactive SQL across multiple data sources. This open source engine supports querying anything, anywhere, and at large scale.

  https://www.kdnuggets.com/2018/04/presto-data-scientists-sql.html

• Big Data Architecture: A Complete and Detailed Overview

  Data scientists may not be as educated or experienced in computer science, programming concepts, devops, site reliability engineering, non-functional requirements, software solution infrastructure, or general software architecture as compared to well-trained or experienced software architects and engineers.

  https://www.kdnuggets.com/2017/09/big-data-architecture-overview.html

• Exclusive Interview: Matei Zaharia, creator of Apache Spark, on Spark, Hadoop, Flink, and Big Data in 2020

  Apache Spark is one the hottest Big Data technologies in 2015. KDnuggets talks to Matei Zaharia, creator of Apache Spark, about key things to know about it, why it is not a replacement for Hadoop, how it is better than Flink, and vision for Big Data in 2020.

  https://www.kdnuggets.com/2015/05/interview-matei-zaharia-creator-apache-spark.html

• Computing Platforms for Analytics, Data Mining, Data Science

  The poll results suggest a split between a majority of data miners and data scientists who work with growing but still "PC-size", small GB-sized data, and a smaller group of Big Data analysts who work with cloud-sized data. Cloud computing, Unix, and especially Mac gained in popularity.

  https://www.kdnuggets.com/2015/04/computing-platforms-analytics-data-mining-data-science.html

• Data Science’s Most Used, Confused, and Abused Jargon

  As data science has spread through the mainstream, so too has a dense vocabulary of ill-defined jargon. In a split-personality post, we offer several perspectives on many of data science's most confused terms.

  https://www.kdnuggets.com/2015/02/data-science-confusing-jargon-abused.html

• Why Azure ML is the Next Big Thing for Machine Learning?

  With advanced capabilities, free access, strong support for R, cloud hosting benefits, drag-and-drop development and many more features, Azure ML is ready to take the consumerization of ML to the next level.

  https://www.kdnuggets.com/2014/11/microsoft-azure-machine-learning.html

• Vector Databases in AI and LLM Use Cases

  Learn about Vectors and How Storing Data Can Be Used in LLM Applications.

  https://www.kdnuggets.com/vector-databases-in-ai-and-llm-use-cases

• Level Up with DataCamp’s New Azure Certification

  Enhance your data profession by learning Azure, a high-demand skill and expertise.

  https://www.kdnuggets.com/level-up-with-datacamps-new-azure-certification

• Geospatial Data Analysis with Geemap

  A Python library for creating interactive maps with Google Earth Engine and ipyleaflet.

  https://www.kdnuggets.com/geospatial-data-analysis-with-geemap

• Mistral 7B-V0.2: Fine-Tuning Mistral’s New Open-Source LLM with Hugging Face

  Access Mistral’s latest open-source model and fine-tune it on a custom dataset.

  https://www.kdnuggets.com/mistral-7b-v02-fine-tuning-mistral-new-open-source-llm-with-hugging-face

• 5 Data Analyst Projects to Land a Job in 2024

  Here’s how to stand out from the competition, impress employers, and get a job in data analytics.

  https://www.kdnuggets.com/5-data-analyst-projects-to-land-a-job-in-2024

• 10 GitHub Repositories to Master MLOps

  Begin your MLOps journey with these comprehensive free resources available on GitHub.

  https://www.kdnuggets.com/10-github-repositories-to-master-mlops

• The 7 Best AI Tools for Data Science Workflow

  Learn about AI productivity tools that will make you a super data scientist.

  https://www.kdnuggets.com/the-7-best-ai-tools-for-data-science-workflow

• Mastering Python for Data Science: Beyond the Basics

  This article serves as a detailed guide on how to master advanced Python techniques for data science. It covers topics such as efficient data manipulation with Pandas, parallel processing with Python, and how to turn models into web services.

  https://www.kdnuggets.com/mastering-python-for-data-science-beyond-the-basics

• Best Free Resources to Learn Data Analysis and Data Science

  This article introduces six top-notch, free data science resources ideal for aspiring data analysts, data scientists, or anyone aiming to enhance their analytical skills.

  https://www.kdnuggets.com/2024/03/365datascience-best-free-resources-learn-data-analysis-data-science

• Prompt Engineering: An Integrated Dream

  Clickbait headlines like "AI's Hottest Job" have promised a career that anyone who knows how to chat with AI could pay a six-figure salary with no computer background. But is this reality, or just another internet pipe dream? Let's ditch the sensationalism and delve into the actual job market data to find out.

  https://www.kdnuggets.com/prompt-engineering-an-integrated-dream

• Sentiment Analysis in Python: Going Beyond Bag of Words

  This code based tutorial provides a brief introduction to Sentiment Analysis, a method used to predict emotions, similar to a digital psychologist.

  https://www.kdnuggets.com/sentiment-analysis-in-python-going-beyond-bag-of-words

• Natural Language Processing: Bridging Human Communication with AI

  The post highlights real-world examples of NLP use cases across industries. It also covers NLP's objectives, challenges, and latest research developments.

  https://www.kdnuggets.com/natural-language-processing-bridging-human-communication-with-ai

• Leveraging AI to Design Fair and Equitable EV Charging Grids

  Learn how AI can be used to design fair and efficient EV charging grids by optimizing their placement and pricing.

  https://www.kdnuggets.com/leveraging-ai-to-design-fair-and-equitable-ev-charging-grids

• Top 16 Technical Data Sources for Advanced Data Science Projects

  Here are data repositories that will up your data science game and improve your data projects.

  https://www.kdnuggets.com/top-16-technical-data-sources-for-advanced-data-science-projects

• Turn Your Laptop Into a Personal Analytics Engine with DuckDB and MotherDuck

  Bring the powerful tools to your laptop.

  https://www.kdnuggets.com/turn-your-laptop-into-a-personal-analytics-engine-with-duckdb-and-motherduck

• What Junior ML Engineers Actually Need to Know to Get Hired?

  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.

  https://www.kdnuggets.com/what-junior-ml-engineers-actually-need-to-know-to-get-hired

• ChatGPT’s New Rival: Google’s Gemini

  Google has introduced a revamped AI model that is said to outperform ChatGPT. Let’s learn more.

  https://www.kdnuggets.com/chatgpts-new-rival-googles-gemini

• Top 10 Kaggle Machine Learning Projects to Become Data Scientist in 2024

  Master Data Science with Top 10 Kaggle ML Projects to become a Data Scientist.

  https://www.kdnuggets.com/top-10-kaggle-machine-learning-projects-to-become-data-scientist-in-2024

• KDnuggets News, December 6: GitHub Repositories to Master Machine Learning • 5 Free Courses to Master Data Engineering

  This week on KDnuggets: Discover GitHub repositories from machine learning courses, bootcamps, books, tools, interview questions, cheat sheets, MLOps platforms, and more to master ML and secure your dream job • Data engineers must prepare and manage the infrastructure and tools necessary for the whole data workflow in a data-driven company • And much, much more!

  https://www.kdnuggets.com/newsletter-n44-2023-12-06

• WTF is the Difference Between GBM and XGBoost?

  See the substantial differences between the famous algorithms.

  https://www.kdnuggets.com/wtf-is-the-difference-between-gbm-and-xgboost

• Types of Visualization Frameworks

  Matching your needs with your ideal visualization framework.

  https://www.kdnuggets.com/types-of-visualization-frameworks

• 5 Free Courses to Master MLOps

  Have you finished learning the basics of machine learning and now wondering what's next? You're in the right place!

  https://www.kdnuggets.com/5-free-courses-to-master-mlops

• Job Trends in Data Analytics: Part 2

  Check out these skillsets in demand for the data analytics job market.

  https://www.kdnuggets.com/job-trends-in-data-analytics-part-2

• Optimizing Data Analytics: Integrating GitHub Copilot in Databricks

  Integrating AI-powered pair programming tools for data analytics in Databricks optimizes and streamlines the development process, freeing up developer time for innovation.

  https://www.kdnuggets.com/optimizing-data-analytics-integrating-github-copilot-in-databricks

• An Honest Comparison of Open Source Vector Databases

  We will explore their use cases, key features, performance metrics, supported programming languages, and more to provide a comprehensive and unbiased overview of each database.

  https://www.kdnuggets.com/an-honest-comparison-of-open-source-vector-databases

• AI and Open Source Software: Separated at Birth?

  In this article, Luis shares with readers his thoughts on the intersection of open source software and machine learning and what the future might bring. Many articles cover how open source software is used by the machine learning community but this post focuses on the similarities between the two areas of practice and what machine learning can and can’t learn from open source software.

  https://www.kdnuggets.com/ai-and-open-source-software-separated-at-birth

• Maximize Performance in Edge AI Applications

  This article provides an overview of the strategies for optimizing AI system performance in edge AI deployments.

  https://www.kdnuggets.com/maximize-performance-in-edge-ai-applications

• The Top 5 Data Management Tools For Your Projects

  See what KDnuggets is recommending for the top 5 cutting-edge tools for cloud, ETL, transformation, master data management, and visualization.

  https://www.kdnuggets.com/top-5-data-management-tools-for-your-projects

• If You Want to Master Generative AI, Ignore All (But Two) Tools

  We have a bad case of generative AI fatigue.

  https://www.kdnuggets.com/if-you-want-to-master-generative-ai-ignore-all-but-two-tools

• Increase Your Callback Rate With A LinkedIn Profile

  It is proven that candidates who include a comprehensive LinkedIn profile in their resume have a 71% higher chance of receiving an interview.

  https://www.kdnuggets.com/increase-your-callback-rate-with-a-linkedin-profile

• Who Will Make Money from the Generative AI Gold Rush?

  Buckle up for the Generative AI gold rush! Will BigTech rule with its picks and shovels? Which startups will strike it rich? Will “copilot for X” be the business strategy to hit pay dirt? How can startups dig moats to keep out other prospectors? And will the US once again have the richest gold seams?

  https://www.kdnuggets.com/2023/08/make-money-generative-ai-gold-rush.html

• The Power of Collaboration: How Open-Source Projects are Advancing AI

  In this article, we explore the profound impact of open-source projects on the creation of innovative AI solutions.

  https://www.kdnuggets.com/2023/08/power-collaboration-opensource-projects-advancing-ai.html

• Things You Should Know When Scaling Your Web Data-Driven Product

  Scaling your data-driven product helps grow your business, but it requires certain expertise. In this article, you will learn how scaling works and what to keep in mind while doing it.

  https://www.kdnuggets.com/2023/08/things-know-scaling-web-datadriven-product.html

• Top 6 Tools to Improve Your Productivity on Snowflake

  The post reviews 6 top tools for improving productivity with Snowflake for data preparation, visualization, integration, BI and governance.

  https://www.kdnuggets.com/2023/08/top-6-tools-improve-productivity-snowflake.html

• This Week in AI, August 7: Generative AI Comes to Jupyter & Stack Overflow • ChatGPT Updates

  "This Week in AI" on KDnuggets provides a weekly roundup of the latest happenings in the world of Artificial Intelligence. Covering a wide range of topics from recent headlines, scholarly articles, educational resources, to spotlight research, the post is designed to keep readers up-to-date and informed about the ever-evolving field of AI.

  https://www.kdnuggets.com/2023/mm/this-week-ai-2023-08-07.html

• This Week in AI, July 31: AI Titans Pledge Responsible Innovation • The Beluga Invasion

  "This Week in AI" on KDnuggets provides a weekly roundup of the latest happenings in the world of Artificial Intelligence. Covering a wide range of topics from recent headlines, scholarly articles, educational resources, to spotlight research, the post is designed to keep readers up-to-date and informed about the ever-evolving field of AI.

  https://www.kdnuggets.com/2023/07/this-week-ai-2023-07-31.html

• Mastering GPUs: A Beginner’s Guide to GPU-Accelerated DataFrames in Python

  RAPIDS cuDF, with its pandas-like API, enables data scientists and engineers to quickly tap into the immense potential of parallel computing on GPUs–with just a few code line changes. Read on for more.

  https://www.kdnuggets.com/2023/07/mastering-gpus-beginners-guide-gpu-accelerated-dataframes-python.html

• Unveiling the Power of Meta’s Llama 2: A Leap Forward in Generative AI?

  This article explores the technical details and implications of Meta's newly released Llama 2, a large language model that promises to revolutionize the field of generative AI. We delve into its capabilities, performance, and potential applications, while also discussing its open-source nature and the company's commitment to safety and transparency.

  https://www.kdnuggets.com/2023/07/unveiling-power-metas-llama-2-leap-forward-generative-ai.html

• Where Does AI Happen?

  Which sector should aspiring researchers flock toward? Academia or industry?

  https://www.kdnuggets.com/2023/07/kdd-where-does-ai-happen.html

• A Practical Guide to Transfer Learning using PyTorch

  In this article, we’ll learn to adapt pre-trained models to custom classification tasks using a technique called transfer learning. We will demonstrate it for an image classification task using PyTorch, and compare transfer learning on 3 pre-trained models, Vgg16, ResNet50, and ResNet152.

  https://www.kdnuggets.com/2023/06/practical-guide-transfer-learning-pytorch.html

• 10 Jupyter Notebook Tips and Tricks for Data Scientists

  Unlock the full potential of Jupyter Notebook with expert tips and techniques, including time-saving shortcuts, powerful magic functions, and advanced features, to boost your productivity.

  https://www.kdnuggets.com/2023/06/10-jupyter-notebook-tips-tricks-data-scientists.html

• ChatGPT in Education: Friend or Foe?

  Students can cheat and ignore critical thinking, or they could have an always-on tutor and be freely curious without judgment. Which side will ChatGPT fall on when it comes to education?

  https://www.kdnuggets.com/2023/05/chatgpt-education-friend-foe.html

• Introducing Healthcare-Specific Large Language Models from John Snow Labs

  John Snow Labs recently released a new LLM called BioGPT-JSL and capabilities tuned specifically to the medical domain. This article summarizes three things you should know about it. 

  https://www.kdnuggets.com/2023/04/john-snow-introducing-healthcare-specific-large-language-models-john-snow-labs.html

• Fine-Tuning OpenAI Language Models with Noisily Labeled Data

  Reduce LLM prediction error by 37% via data-centric AI.

  https://www.kdnuggets.com/2023/04/finetuning-openai-language-models-noisily-labeled-data.html

• What Is ChatGPT Doing and Why Does It Work?

  In this article, we will explain how ChatGPT works and why it is able to produce coherent and diverse conversations.

  https://www.kdnuggets.com/2023/04/chatgpt-work.html

• Beyond Accuracy: Evaluating & Improving a Model with the NLP Test Library

  John Snow Labs has learned a lot about testing and delivering Responsible NLP models: not only in terms of policies and goals, but by building day-to-day tools for data scientists. The nlptest library aims to share these tools with the open-source community.

  https://www.kdnuggets.com/2023/04/john-snow-beyond-accuracy-nlp-test-library.html

• Introducing the Testing Library for Natural Language Processing

  Deliver reliable, safe and effective NLP models.

  https://www.kdnuggets.com/2023/04/introducing-testing-library-natural-language-processing.html

• Reading Minds with AI: Researchers Translate Brain Waves to Images

  Two researchers from Osaka University were able to reconstruct highly accurate images from human brain activity obtained by fMRI. Read this article if you are curious to find out what all the hype is about.

  https://www.kdnuggets.com/2023/03/reading-minds-ai-researchers-translate-brain-waves-images.html

• 9 Top Platforms to Practice Key Data Science Skills

  Which platforms would I recommend as a go-to for learning and practicing data science skills? The list would change every day, depending on my mood. Here’s today’s list with an overview of each platform.

  https://www.kdnuggets.com/2023/03/9-top-platforms-practice-key-data-science-skills.html

• Must Read NLP Papers from the Last 12 Months

  The era of large language models is here now.

  https://www.kdnuggets.com/2023/03/must-read-nlp-papers-last-12-months.html

• 5 Data Analysis Projects For Beginners

  Are you a data analyst newbie looking to boost your resume to land your first job? If yes, then up your game as a beginner with these 5 projects that you can’t afford to miss.

  https://www.kdnuggets.com/2023/02/5-data-analysis-projects-beginners.html

• Tapping into the Potential of Data Products in 2023

  Learn how data can be treated as a product and how it can be used to derive value.

  https://www.kdnuggets.com/2023/01/tapping-potential-data-products-2023.html

• Setup and use JupyterHub (TLJH) on AWS EC2

  JupyterHub is a multi-user, container-friendly version of the Jupyter Notebook. However, it can be difficult to setup. This blog post will make you less likely to run into issues in this 15+ step process.

  https://www.kdnuggets.com/2023/01/setup-jupyterhub-tljh-aws-ec2.html

• From Data Collection to Model Deployment: 6 Stages of a Data Science Project

  Here are 6 stages of a novel Data Science Project; From Data Collection to Model in Production, backed by research and examples.

  https://www.kdnuggets.com/2023/01/data-collection-model-deployment-6-stages-data-science-project.html

• Top Data Python Packages to Know in 2023

  These Python packages would improve your data workflow.

  https://www.kdnuggets.com/2023/01/top-data-python-packages-know-2023.html

• Key Data Science, Machine Learning, AI and Analytics Developments of 2022

  It's the end of the year, and so it's time for KDnuggets to assemble a team of experts and get to the bottom of what the most important data science, machine learning, AI and analytics developments of 2022 were.

  https://www.kdnuggets.com/2022/12/key-data-science-machine-learning-ai-analytics-developments-2022.html

• Learn Data Science From These GitHub Repositories

  Kickstart your data science career with these curated GitHub repositories.

  https://www.kdnuggets.com/2022/12/learn-data-science-github-repositories.html

• Sentiment Analysis on Encrypted Data with Homomorphic Encryption

  This blog post uses the Concrete-ML library, allowing data scientists to use machine learning models in fully homomorphic encryption (FHE) settings without any prior knowledge of cryptography. We provide a practical tutorial on how to use the library to build a sentiment analysis model on encrypted data.

  https://www.kdnuggets.com/2022/12/zama-sentiment-analysis-encrypted-data-homomorphic-encryption.html

• How to Prepare for a Data Science Interview

  When interviewing for a data scientist, it’s crucial to know how and what to prepare to be successful. But success also lies in knowing what not to prepare.

  https://www.kdnuggets.com/2022/12/prepare-data-science-interview.html

• A Brief Introduction to Kalman Filters

  What you can’t observe, you ought to estimate. Human evolution is based on this keen interest in measurement. But what are the quantities or phenomena which you can’t observe or measure with certainty? Learn this and more about Kalman Filter which is the most widely used algorithm to estimate a true quantity.

  https://www.kdnuggets.com/2022/12/brief-introduction-kalman-filters.html

• Is OLAP Dead?

  OLAP enables citizen analysts to quickly, efficiently, and cost-effectively uncover new business insights at a reduced time-to-value.

  https://www.kdnuggets.com/2022/10/olap-dead.html

• 7 Free Platforms for Building a Strong Data Science Portfolio

  Outshine others and increase your odds of getting hired by maintaining a data science portfolio with projects, resumes, blogs, and reports.

  https://www.kdnuggets.com/2022/10/7-free-platforms-building-strong-data-science-portfolio.html

• 11 Questions About Data Engineers: What’s the profession about, and where’s it heading?

  I hope my answers will be useful to novice data engineers and anyone interested in data engineering.

  https://www.kdnuggets.com/2022/10/11-questions-data-engineers-profession-heading.html

• 7 Things You Didn’t Know You Could do with a Low Code Tool

  Surprisingly easy solutions for complex data problems.

  https://www.kdnuggets.com/2022/09/7-things-didnt-know-could-low-code-tool.html

• The 5 Best Places To Host Your Data Science Portfolio

  How can you showcase your data scientist skills and abilities? The answer to this question is online platforms where you can publish your portfolio and seize opportunities.

  https://www.kdnuggets.com/2022/07/5-best-places-host-data-science-portfolio.html

• Data Preparation with SQL Cheatsheet

  If your raw data is in a SQL-based data lake, why spend the time and money to export the data into a new platform for data prep?

  https://www.kdnuggets.com/2021/05/data-preparation-sql-cheat-sheet.html

• Generate Synthetic Time-series Data with Open-source Tools

  An introduction to the generative adversarial network model DoppelGANger, and how you can use a new open-source PyTorch implementation of it to create high-quality synthetic time-series data.

  https://www.kdnuggets.com/2022/06/generate-synthetic-timeseries-data-opensource-tools.html

• 6 Things You Need To Know About Data Management And Why It Matters For Computer Vision

  This article will explore a few areas that we feel are essential when assessing data management solutions for computer vision.

  https://www.kdnuggets.com/2022/05/6-things-need-know-data-management-matters-computer-vision.html

• oBERT: Compound Sparsification Delivers Faster Accurate Models for NLP

  Discover "compound sparsification" and how to apply it to BERT models for 10x compression and GPU-level latency on commodity CPUs.

  https://www.kdnuggets.com/2022/05/obert-compound-sparsification-delivers-faster-accurate-models-nlp.html

• 5 Free Hosting Platform For Machine Learning Applications

  Learn about the free and easy-to-deploy hosting platform for your machine learning projects.

  https://www.kdnuggets.com/2022/05/5-free-hosting-platform-machine-learning-applications.html

• An Overview of Mercury: Creating Data Science Portfolio and Notebook Based WebApps

  Turn your dull Jupyter notebooks into interactive web apps by adding a YAML header and sharing it with your friends and colleagues. You can also use Mercury to create your data science portfolio, which consists of a resume and projects.

  https://www.kdnuggets.com/2022/05/overview-mercury-creating-data-science-portfolio-notebook-based-webapps.html

• How to Build Strong Data Science Portfolio as a Beginner

  After learning the basics of data science, you can start to work on real-world problems. But how do you showcase your work? In this article, we are going to learn a unique way to create a data science portfolio.

  https://www.kdnuggets.com/2021/10/strong-data-science-portfolio-as-beginner.html

• Top 10 Machine Learning Demos: Hugging Face Spaces Edition

  Hugging Face Spaces allows you to have an interactive experience with the machine learning models, and we will be discovering the best application to get some inspiration.

  https://www.kdnuggets.com/2022/05/top-10-machine-learning-demos-hugging-face-spaces-edition.html

• The Complete Collection Of Data Repositories – Part 2

  Check out the collection of the best data repositories on healthcare, natural language, neuroscience, physics, social network, sports, time series, transportation, miscellaneous, and super data repositories.

  https://www.kdnuggets.com/2022/04/complete-collection-data-repositories-part-2.html

• A New Way of Managing Deep Learning Datasets

  Create, version-control, query, and visualize image, audio, and video datasets using Hub 2.0 by Activeloop.

  https://www.kdnuggets.com/2022/03/new-way-managing-deep-learning-datasets.html

• Building a Geospatial Application in Python with Google Earth Engine and Greppo

  In this blog, you will see how to build a web-application with Greppo and Google Earth using Python.

  https://www.kdnuggets.com/2022/03/building-geospatial-application-python-google-earth-engine-greppo.html

• 8 Women in AI Who Are Striving to Humanize the World

  Some exceptional female researchers and engineers are working on projects to make the world a better place with the help of AI, data science, and machine learning.

  https://www.kdnuggets.com/2021/03/8-women-ai-striving-humanize-world.html

• How to Create a Dataset for Machine Learning

  Datasets - properly curated and labeled - remain a scarce resource. What can be done about this?

  https://www.kdnuggets.com/2022/02/create-dataset-machine-learning.html

• Design Patterns in Machine Learning for MLOps

  This article outlines some of the most common design patterns encountered when creating successful Machine Learning solutions.

  https://www.kdnuggets.com/2022/02/design-patterns-machine-learning-mlops.html

• The Challenges of Being a Data Scientist

  According to a Stack Overflow survey, 13.2% of the data scientists are looking for a new job, as they are not satisfied in their current role. So why is this happening? What are the challenges Data Scientists are facing?

  https://www.kdnuggets.com/2022/02/data-scientist-challenges.html

• No Brainer AutoML with AutoXGB

  Learn how to train, optimize, and build API with a few lines of code using AutoXGB.

  https://www.kdnuggets.com/2022/02/no-brainer-automl-autoxgb.html