Search results for public cloud

Found 432 documents, 5946 searched:

• 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

• From Oracle to Databases for AI: The Evolution of Data Storage

  From Oracle, to NoSQL databases, and beyond, read about data management solutions from the early days of the RBDMS to those supporting AI applications.

  https://www.kdnuggets.com/2022/02/oracle-databases-ai-evolution-data-storage.html

• Unstructured Data: The Must-Have For Analytics In 2022

  Let's investigate the current need that enterprise organizations have to rapidly parse through unstructured data and examine several data management trends that are highly relevant in 2022.

  https://www.kdnuggets.com/2022/01/unstructured-data-analytics-2022.html

• How to Set Up Your Data Science Stack on a Budget

  Whether you’re working independently or setting up a stack for a company, you need an affordable stack option. Here’s how you can set up your stack without spending too much.

  https://www.kdnuggets.com/2022/01/data-science-stack-budget.html

• Top Programming Languages and Their Uses

  The landscape of programming languages is rich and expanding, which can make it tricky to focus on just one or another for your career. We highlight some of the most popular languages that are modern, widely used, and come with loads of packages or libraries that will help you be more productive and efficient in your work.

  https://www.kdnuggets.com/2021/05/top-programming-languages.html

• How to Process a DataFrame with Millions of Rows in Seconds

  TLDR; process it with a new Python Data Processing Engine in the Cloud.

  https://www.kdnuggets.com/2022/01/process-dataframe-millions-rows-seconds.html

• Learn Deep Learning by Building 15 Neural Network Projects in 2022

  Here are 15 neural network projects you can take on in 2022 to build your skills, your know-how, and your portfolio.

  https://www.kdnuggets.com/2022/01/15-neural-network-projects-build-2022.html

• The Easiest Way to Make Beautiful Interactive Visualizations With Pandas

  Check out these one-liner interactive visualization with Pandas in Python.

  https://www.kdnuggets.com/2021/12/easiest-way-make-beautiful-interactive-visualizations-pandas.html

• Cutting Down Implementation Time by Integrating Jupyter and KNIME

  Are you a KNIME fan or a Jupyter fan? Well, here you don’t have to choose.

  https://www.kdnuggets.com/2021/12/cutting-implementation-time-integrating-jupyter-knime.html

• Data Science & Analytics Industry Main Developments in 2021 and Key Trends for 2022

  We have solicited insights from experts at industry-leading companies, asking: "What were the main AI, Data Science, Machine Learning Developments in 2021 and what key trends do you expect in 2022?" Read their opinions here.

  https://www.kdnuggets.com/2021/12/developments-predictions-data-science-analytics-industry.html

• 12 Tips: From Data Analyst to Startup Co-Founder

  Thinking about taking your data science expertise to a new level of creating a start-up company? These tips -- learned from experience -- can help you forge an early path toward success.

  https://www.kdnuggets.com/2021/12/12-tips-data-analyst-to-co-founder.html

• Analyzing Scientific Articles with fine-tuned SciBERT NER Model and Neo4j

  In this article, we will be analyzing a dataset of scientific abstracts using the Neo4j Graph database and a fine-tuned SciBERT model.

  https://www.kdnuggets.com/2021/12/analyzing-scientific-articles-finetuned-scibert-ner-model-neo4j.html

• KDnuggets: Personal History and Nuggets of Experience

  After 28+ years of publishing and editing KDnuggets, I am retiring and transitioning KDnuggets to Matthew Mayo, who will become the new editor-in-chief. I want to share with you my story of KDnuggets and highlight some of the useful nuggets of experience I learned along this amazing journey.

  https://www.kdnuggets.com/2021/11/kdnuggets-history.html

• How to Build Data Frameworks with Open Source Tools to Enhance Agility and Security

  Let’s take a look at how to harness open source tools to build your data frameworks.

  https://www.kdnuggets.com/2021/10/build-data-frameworks-open-source-tools-agility-security.html

• Serving ML Models in Production: Common Patterns

  Over the past couple years, we've seen 4 common patterns of machine learning in production: pipeline, ensemble, business logic, and online learning. In the ML serving space, implementing these patterns typically involves a tradeoff between ease of development and production readiness. Ray Serve was built to support these patterns by being both easy to develop and production ready.

  https://www.kdnuggets.com/2021/10/serving-ml-models-production-common-patterns.html

• What is Clustering and How Does it Work?

  Let us examine how clusters with different properties are produced by different clustering algorithms. In particular, we give an overview of three clustering methods: k-Means clustering, hierarchical clustering, and DBSCAN.

  https://www.kdnuggets.com/2021/10/clustering-what-is-how-works.html

• Create Synthetic Time-series with Anomaly Signatures in Python

  A simple and intuitive way to create synthetic (artificial) time-series data with customized anomalies — particularly suited to industrial applications.

  https://www.kdnuggets.com/2021/10/synthetic-time-series-anomaly-signatures-python.html

• What 2 years of self-teaching data science taught me

  Many of us self-learn data science from the very beginning. While continuing to self-learn on demand is crucial, especially after you become a professional, there can be many pitfalls early on for learning the wrong way or missing out on key ideas that are important for the real-world application of data science.

  https://www.kdnuggets.com/2021/09/2-years-self-teaching-data-science.html

• How to Create Stunning Web Apps for your Data Science Projects">How to Create Stunning Web Apps for your Data Science Projects

  Data scientists do not have to learn HTML, CSS, and JavaScript to build web pages.

  https://www.kdnuggets.com/2021/09/create-stunning-web-apps-data-science-projects.html

• Stack Overflow Survey Data Science Highlights

  The results of the 2021 Stack Overflow Developer Survey were recently released, which is a fascinating snapshot of today's developers and the tools they are using. Have a look at some selections from the report, particularly those which may be of interest to data professionals.

  https://www.kdnuggets.com/2021/08/stack-overflow-survey-data-science-highlights.html

• 15 Things I Look for in Data Science Candidates

  This article presents advice for anyone looking or hiring for data science jobs, written by someone with practical and useful insight.

  https://www.kdnuggets.com/2021/08/15-things-data-science-candidates.html

• Amazon Web Services Webinar: Accelerating clinical trial and biomedical development processes with healthcare data

  Join this webinar on August 27 to learn how to leverage external healthcare datasets to make faster decisions with greater accuracy – accelerating biomedical development and improving patient welfare.

  https://www.kdnuggets.com/2021/08/aws-webinar-clinical-trial-biomedical-development-healthcare.html

• Writing Your First Distributed Python Application with Ray

  Using Ray, you can take Python code that runs sequentially and transform it into a distributed application with minimal code changes. Read on to find out why you should use Ray, and how to get started.

  https://www.kdnuggets.com/2021/08/distributed-python-application-ray.html

• MLOps And Machine Learning Roadmap

  A 16–20 week roadmap to review machine learning and learn MLOps.

  https://www.kdnuggets.com/2021/08/mlops-machine-learning-roadmap.html

• Bootstrap a Modern Data Stack in 5 minutes with Terraform">Bootstrap a Modern Data Stack in 5 minutes with Terraform

  What is a Modern Data Stack and how do you deploy one? This guide will motivate you to start on this journey with setup instructions for Airbyte, BigQuery, dbt, Metabase, and everything else you need using Terraform.

  https://www.kdnuggets.com/2021/08/bootstrap-modern-data-stack-terraform.html

• MLOps Best Practices

  Many technical challenges must be overcome to achieve successful delivery of machine learning solutions at scale. This article shares best practices we encountered while architecting and applying a model deployment platform within a large organization, including required functionality, the recommendation for a scalable deployment pattern, and techniques for testing and performance tuning models to maximize platform throughput.

  https://www.kdnuggets.com/2021/07/mlops-best-practices.html

• Building Machine Learning Pipelines using Snowflake and Dask

  In this post, I want to share some of the tools that I have been exploring recently and show you how I use them and how they helped improve the efficiency of my workflow. The two I will talk about in particular are Snowflake and Dask. Two very different tools but ones that complement each other well especially as part of the ML Lifecycle.

  https://www.kdnuggets.com/2021/07/building-machine-learning-pipelines-snowflake-dask.html

• ColabCode: Deploying Machine Learning Models From Google Colab

  New to ColabCode? Learn how to use it to start a VS Code Server, Jupyter Lab, or FastAPI.

  https://www.kdnuggets.com/2021/07/colabcode-deploying-machine-learning-models-google-colab.html

• High-Performance Deep Learning: How to train smaller, faster, and better models – Part 5

  Training efficient deep learning models with any software tool is nothing without an infrastructure of robust and performant compute power. Here, current software and hardware ecosystems are reviewed that you might consider in your development when the highest performance possible is needed.

  https://www.kdnuggets.com/2021/07/high-performance-deep-learning-part5.html

• 7 Open Source Libraries for Deep Learning Graphs

  In this article we’ll go through 7 up-and-coming open source libraries for graph deep learning, ranked in order of increasing popularity.

  https://www.kdnuggets.com/2021/07/7-open-source-libraries-deep-learning-graphs.html

• Become an Analytics Engineer in 90 Days">Become an Analytics Engineer in 90 Days

  A new role of the Analytics Engineer is an exciting opportunity that crosses the skill sets of a Data Analyst and Data Engineer. Here, we describe how this position can evolve at an organization, and recommend self-learning resources that can be used to prepare for the multifaceted responsibilities.

  https://www.kdnuggets.com/2021/07/become-analytics-engineer-90-days.html

• High-Performance Deep Learning: How to train smaller, faster, and better models – Part 3

  Now that you are ready to efficiently build advanced deep learning models with the right software and hardware tools, the techniques involved in implementing such efforts must be explored to improve model quality and obtain the performance that your organization desires.

  https://www.kdnuggets.com/2021/07/high-performance-deep-learning-part3.html

• High-Performance Deep Learning: How to train smaller, faster, and better models – Part 2

  As your organization begins to consider building advanced deep learning models with efficiency in mind to improve the power delivered through your solutions, the software and hardware tools required for these implementations are foundational to achieving high-performance.

  https://www.kdnuggets.com/2021/06/high-performance-deep-learning-part2.html

• High Performance Deep Learning, Part 1

  Advancing deep learning techniques continue to demonstrate incredible potential to deliver exciting new AI-enhanced software and systems. But, training the most powerful models is expensive--financially, computationally, and environmentally. Increasing the efficiency of such models will have profound impacts in many ways, so developing future models with this intension in mind will only help to further expand the reach, applicability, and value of what deep learning has to offer.

  https://www.kdnuggets.com/2021/06/efficiency-deep-learning-part1.html

• Awesome list of datasets in 100+ categories

  With an estimated 44 zettabytes of data in existence in our digital world today and approximately 2.5 quintillion bytes of new data generated daily, there is a lot of data out there you could tap into for your data science projects. It's pretty hard to curate through such a massive universe of data, but this collection is a great start. Here, you can find data from cancer genomes to UFO reports, as well as years of air quality data to 200,000 jokes. Dive into this ocean of data to explore as you learn how to apply data science techniques or leverage your expertise to discover something new.

  https://www.kdnuggets.com/2021/05/awesome-list-datasets.html

• 7 Must-Haves in your Data Science CV

  If you are looking for a new role as a Data Scientist -- either as a first job fresh out of school, a career change, or a shift to another organization -- then check off as many of these critical points as possible to stand out in the crowd and pass the hiring manager's initial CV screen.

  https://www.kdnuggets.com/2021/04/7-must-haves-data-science-cv.html

• Why So Many Data Scientists Quit Good Jobs at Great Companies

  The role of the Data Scientist continues to offer many great opportunities as a career. However, the 'sexiest job of the 21st century' has lost some of its appeal because of unrealized expectations and how organizations might leverage this type of work. Having a better understanding of how data science typically plays out in the business world can help you achieve the success you want.

  https://www.kdnuggets.com/2021/03/why-data-scientists-quit-good-jobs.html

• Data Science Curriculum for Professionals

  If you are looking to expand or transition your current professional career that is buried in spreadsheet analysis into one powered by data science, then you are in for an exciting but complex journey with much to explore and master. To begin your adventure, following this complete road map to guide you from a gnome in the forest of spreadsheets to an AI wizard known far and wide throughout the kingdom.

  https://www.kdnuggets.com/2021/03/data-science-curriculum-professionals.html

• Top 10 Python Libraries Data Scientists should know in 2021">Top 10 Python Libraries Data Scientists should know in 2021

  So many Python libraries exist that offer powerful and efficient foundations for supporting your data science work and machine learning model development. While the list may seem overwhelming, there are certain libraries you should focus your time on, as they are some of the most commonly used today.

  https://www.kdnuggets.com/2021/03/top-10-python-libraries-2021.html

• Top YouTube Machine Learning Channels

  These are the top 15 YouTube channels for machine learning as determined by our stated criteria, along with some additional data on the channels to help you decide if they may have some content useful for you.

  https://www.kdnuggets.com/2021/03/top-youtube-machine-learning-channels.html

• Must Know for Data Scientists and Data Analysts: Causal Design Patterns">Must Know for Data Scientists and Data Analysts: Causal Design Patterns

  Industry is a prime setting for observational causal inference, but many companies are blind to causal measurement beyond A/B tests. This formula-free primer illustrates analysis design patterns for measuring causal effects from observational data.

  https://www.kdnuggets.com/2021/03/causal-design-patterns.html

• Data Science Learning Roadmap for 2021">Data Science Learning Roadmap for 2021

  Venturing into the world of Data Science is an exciting, interesting, and rewarding path to consider. There is a great deal to master, and this self-learning recommendation plan will guide you toward establishing a solid understanding of all that is foundational to data science as well as a solid portfolio to showcase your developed expertise.

  https://www.kdnuggets.com/2021/02/data-science-learning-roadmap-2021.html

• GPT-2 vs GPT-3: The OpenAI Showdown

  Thanks to the diversity of the dataset used in the training process, we can obtain adequate text generation for text from a variety of domains. GPT-2 is 10x the parameters and 10x the data of its predecessor GPT.

  https://www.kdnuggets.com/2021/02/gpt2-gpt3-openai-showdown.html

• Past 2021 Meetings / Online Events on AI, Analytics, Big Data, Data Science, and Machine Learning

  Past | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec Read more »

  https://www.kdnuggets.com/meetings/past-meetings-2021.html

• Machine learning is going real-time

  Extracting immediate predictions from machine learning algorithms on the spot based on brand-new data can offer a next level of interaction and potential value to its consumers. The infrastructure and tech stack required to implement such real-time systems is also next level, and many organizations -- especially in the US -- seem to be resisting. But, what even is real-time ML, and how can it deliver a better experience?

  https://www.kdnuggets.com/2021/01/machine-learning-real-time.html

• How to Get a Job as a Data Engineer

  Data engineering skills are currently in high demand. If you are looking for career prospects in this fast-growing profession, then these 10 skills and key factors will help you prepare to land an entry-level position in this field.

  https://www.kdnuggets.com/2021/01/get-job-as-data-engineer.html

• Generating Beautiful Neural Network Visualizations">Generating Beautiful Neural Network Visualizations

  If you are looking to easily generate visualizations of neural network architectures, PlotNeuralNet is a project you should check out.

  https://www.kdnuggets.com/2020/12/generating-beautiful-neural-network-visualizations.html

• Top 9 Data Science Courses to Learn Online

  Learn Data Science from these top courses. Details like cost and course duration are included.

  https://www.kdnuggets.com/2020/12/simplilearn-top-9-data-science-courses-online.html

• Production Machine Learning Monitoring: Outliers, Drift, Explainers & Statistical Performance

  A practical deep dive on production monitoring architectures for machine learning at scale using real-time metrics, outlier detectors, drift detectors, metrics servers and explainers.

  https://www.kdnuggets.com/2020/12/production-machine-learning-monitoring-outliers-drift-explainers-statistical-performance.html

• Navigate the road to Responsible AI

  Deploying AI ethically and responsibly will involve cross-functional team collaboration, new tools and processes, and proper support from key stakeholders.

  https://www.kdnuggets.com/2020/12/navigate-road-responsible-ai.html

• Main 2020 Developments and Key 2021 Trends in AI, Data Science, Machine Learning Technology">Main 2020 Developments and Key 2021 Trends in AI, Data Science, Machine Learning Technology

  Our panel of leading experts reviews 2020 main developments and examines the key trends in AI, Data Science, Machine Learning, and Deep Learning Technology.

  https://www.kdnuggets.com/2020/12/developments-trends-ai-data-science-machine-learning-technology.html

• Is Data Science for Me? 14 Self-examination Questions to Consider">Is Data Science for Me? 14 Self-examination Questions to Consider

  You are intrigued by this exciting new field of Data Science, and you think you want in on the action. The demand remains very high and the salaries are strong. Before taking the leap onto this path, these questions will help you evaluate if you are ready for the challenges and opportunities.

  https://www.kdnuggets.com/2020/11/data-science-14-self-examination-questions.html

• My Data Science Online Learning Journey on Coursera

  Check out the author's informative list of courses and specializations on Coursera taken to get started on their data science and machine learning journey.

  https://www.kdnuggets.com/2020/11/data-science-online-learning-journey-coursera.html

• 2 Coding-free Ways to Extract Content From Websites to Boost Web Traffic

  There are 2 main coding-free solutions for extracting content from websites to build your content base: use web scraping tools and use content aggregation tools. We review top choices.

  https://www.kdnuggets.com/2020/11/octoparse-coding-free-extract-content.html

• How Automation Is Improving the Role of Data Scientists

  Here is an overview of 5 ways that data automation will enhance how scientists spend their time and improve the results they get.

  https://www.kdnuggets.com/2020/10/automation-improving-data-scientists.html

• Deploying Secure and Scalable Streamlit Apps on AWS with Docker Swarm, Traefik and Keycloak

  If you are a data scientist who just wants to get the work done but doesn’t necessarily want to go down the DevOps rabbit hole, this tutorial offers a relatively straightforward deployment solution leveraging Docker Swarm and Traefik, with an option of adding user authentication with Keycloak.

  https://www.kdnuggets.com/2020/10/deploying-secure-scalable-streamlit-apps-aws-docker-swarm-traefik-keycloak.html

• 5 Must-Read Data Science Papers (and How to Use Them)

  Keeping ahead of the latest developments in a field is key to advancing your skills and your career. Five foundational ideas from recent data science papers are highlighted here with tips on how to leverage these advancements in your work, and keep you on top of the machine learning game.

  https://www.kdnuggets.com/2020/10/5-must-read-data-science-papers.html

• Software Engineering Tips and Best Practices for Data Science">Software Engineering Tips and Best Practices for Data Science

  Bringing your work as a Data Scientist into the real-world means transforming your experiments, test, and detailed analysis into great code that can be deployed as efficient and effective software solutions. You must learn how to enable your machine learning algorithms to integrate with IT systems by taking them out of your notebooks and delivering them to the business by following software engineering standards.

  https://www.kdnuggets.com/2020/10/software-engineering-best-practices-data-science.html

• 5 Best Practices for Putting Machine Learning Models Into Production

  Our focus for this piece is to establish the best practices that make an ML project successful.

  https://www.kdnuggets.com/2020/10/5-best-practices-machine-learning-models-production.html

• 6 Lessons Learned in 6 Months as a Data Scientist

  When transitioning into a Data Science career, a new mindset toward collaboration, data, and reporting is required. Learn from these recommendations on approaches you should consider to successfully develop into your dream job.

  https://www.kdnuggets.com/2020/10/6-lessons-6-months-data-scientist.html

• Unpopular Opinion – Data Scientists Should Be More End-to-End

  Can a do-it-all Data Scientist really be more effective at delivering new value from data? While it might sound exhausting, important efficiencies can exist that might bring better value to the business even faster.

  https://www.kdnuggets.com/2020/09/data-scientists-should-be-more-end-to-end.html

• Autograd: The Best Machine Learning Library You’re Not Using?">Autograd: The Best Machine Learning Library You’re Not Using?

  If there is a Python library that is emblematic of the simplicity, flexibility, and utility of differentiable programming it has to be Autograd.

  https://www.kdnuggets.com/2020/09/autograd-best-machine-learning-library-not-using.html

• DIY Election Fraud Analysis Using Benford’s Law

  In this article, we will talk about a Do-It-Yourself approach towards election analysis and coming to a conclusion whether the elections were conducted fairly or not.

  https://www.kdnuggets.com/2020/09/diy-election-fraud-analysis-benfords-law.html

• 9 Developing Data Science & Analytics Job Trends

  With so much disruption in 2020 already, a recent report by Burtch Works looks ahead to next year and beyond, and shares insights about how today's hiring market trends may impact our work lives for years to come.

  https://www.kdnuggets.com/2020/09/data-science-analytics-job-trends.html

• Working with Spark, Python or SQL on Azure Databricks

  Here we look at some ways to interchangeably work with Python, PySpark and SQL using Azure Databricks, an Apache Spark-based big data analytics service designed for data science and data engineering offered by Microsoft.

  https://www.kdnuggets.com/2020/08/spark-python-sql-azure-databricks.html

• Data Science Meets Devops: MLOps with Jupyter, Git, and Kubernetes

  An end-to-end example of deploying a machine learning product using Jupyter, Papermill, Tekton, GitOps and Kubeflow.

  https://www.kdnuggets.com/2020/08/data-science-meets-devops-mlops-jupyter-git-kubernetes.html

• Top Google AI, Machine Learning Tools for Everyone">Top Google AI, Machine Learning Tools for Everyone

  Google is much more than a search company. Learn about all the tools they are developing to help turn your ideas into reality through Google AI.

  https://www.kdnuggets.com/2020/08/top-google-ai-machine-learning-tools.html

• The List of Top 10 Lists in Data Science">The List of Top 10 Lists in Data Science

  The list of Top 10 lists that Data Scientists -- from enthusiasts to those who want to jump start a career -- must know to smoothly navigate a path through this field.

  https://www.kdnuggets.com/2020/08/top-10-lists-data-science.html

• GitHub is the Best AutoML You Will Ever Need

  This article uses PyCaret 2.0, an open source, low-code machine learning library in Python to develop a simple AutoML solution and deploy it as a Docker container using GitHub actions.

  https://www.kdnuggets.com/2020/08/github-best-automl-ever-need.html

• 10 Use Cases for Privacy-Preserving Synthetic Data

  This article presents 10 use-cases for synthetic data, showing how enterprises today can use this artificially generated information to train machine learning models or share data externally without violating individuals' privacy.

  https://www.kdnuggets.com/2020/08/10-use-cases-privacy-preserving-synthetic-data.html

• Why You Should Get Google’s New Machine Learning Certificate

  Google is offering a new ML Engineer certificate, geared towards professionals who want to display their competency in topics like distributed model training and scaling to production. Is it worth it?

  https://www.kdnuggets.com/2020/07/googles-new-machine-learning-certificate.html

• Powerful CSV processing with kdb+

  This article provides a glimpse into the available tools to work with CSV files and describes how kdb+ and its query language q raise CSV processing to a new level of performance and simplicity.

  https://www.kdnuggets.com/2020/07/powerful-csv-processing-kdb.html

• 10 Steps for Tackling Data Privacy and Security Laws in 2020

  Data privacy laws, such as the CCPA, GDPR, and HIPAA, are here to stay and significantly impact everyone in the digital era. These steps will guide organizations to prepare for compliance and ensure they support the fundamental privacy rights of their customers and users.

  https://www.kdnuggets.com/2020/07/10-steps-data-privacy-security-laws.html

• Building a REST API with Tensorflow Serving (Part 2)

  This post is the second part of the tutorial of Tensorflow Serving in order to productionize Tensorflow objects and build a REST API to make calls to them.

  https://www.kdnuggets.com/2020/07/building-rest-api-tensorflow-serving-part-2.html

• What I learned from looking at 200 machine learning tools

  While hundreds of machine learning tools are available today, the ML software landscape may still be underdeveloped with more room to mature. This review considers the state of ML tools, existing challenges, and which frameworks are addressing the future of machine learning software.

  https://www.kdnuggets.com/2020/07/200-machine-learning-tools.html

• A Layman’s Guide to Data Science. Part 3: Data Science Workflow">A Layman’s Guide to Data Science. Part 3: Data Science Workflow

  Learn and appreciate the typical workflow for a data science project, including data preparation (extraction, cleaning, and understanding), analysis (modeling), reflection (finding new paths), and communication of the results to others.

  https://www.kdnuggets.com/2020/07/laymans-guide-data-science-workflow.html

• Deploy Machine Learning Pipeline on AWS Fargate">Deploy Machine Learning Pipeline on AWS Fargate

  A step-by-step beginner’s guide to containerize and deploy ML pipeline serverless on AWS Fargate.

  https://www.kdnuggets.com/2020/07/deploy-machine-learning-pipeline-aws-fargate.html

• Best Machine Learning Youtube Videos Under 10 Minutes

  The Youtube videos on this list cover concepts such as what machine learning is, the basics of natural language processing, how computer vision works, and machine learning in video games.

  https://www.kdnuggets.com/2020/06/best-machine-learning-youtube-videos-under-10-minutes.html

• Taming Complexity in MLOps

  A greatly expanded v2.0 of the open-source Orbyter toolkit helps data science teams continue to streamline machine learning delivery pipelines, with an emphasis on seamless deployment to production.

  https://www.kdnuggets.com/2020/05/taming-complexity-mlops.html

• Deepmind’s Gaming Streak: The Rise of AI Dominance

  There is still a long way to go before machine agents match overall human gaming prowess, but Deepmind’s gaming research focus has shown a clear progression of substantial progress.

  https://www.kdnuggets.com/2020/05/deepmind-gaming-ai-dominance.html

• Build and deploy your first machine learning web app">Build and deploy your first machine learning web app

  A beginner’s guide to train and deploy machine learning pipelines in Python using PyCaret.

  https://www.kdnuggets.com/2020/05/build-deploy-machine-learning-web-app.html

• AI and Machine Learning for Healthcare">AI and Machine Learning for Healthcare

  Traditional business and technology sectors are not the only fields being impacted by AI. Healthcare is a field that is thought to be highly suitable for the applications of AI tools and techniques.

  https://www.kdnuggets.com/2020/05/ai-machine-learning-healthcare.html

• Best Coronavirus Projections, Predictions, Dashboards and Data Resources

  Check out this curated collection of coronavirus-related projections, dashboards, visualizations, and data that we have encountered on the internet.

  https://www.kdnuggets.com/2020/05/best-coronavirus-projections-predictions-dashboards-data-resources.html

• Dockerize Jupyter with the Visual Debugger

  A step by step guide to enable and use visual debugging in Jupyter in a docker container.

  https://www.kdnuggets.com/2020/04/dockerize-jupyter-visual-debugger.html

• Better notebooks through CI: automatically testing documentation for graph machine learning

  In this article, we’ll walk through the detailed and helpful continuous integration (CI) that supports us in keeping StellarGraph’s demos current and informative.

  https://www.kdnuggets.com/2020/04/better-notebooks-through-ci-automatically-testing-documentation-graph-machine-learning.html

• Why and How to Use Dask with Big Data

  The Pandas library for Python is a game-changer for data preparation. But, when the data gets big, really big, then your computer needs more help to efficiency handle all that data. Learn more about how to use Dask and follow a demo to scale up your Pandas to work with Big Data.

  https://www.kdnuggets.com/2020/04/dask-big-data.html

• 10 Must-read Machine Learning Articles (March 2020)">10 Must-read Machine Learning Articles (March 2020)

  This list will feature some of the recent work and discoveries happening in machine learning, as well as guides and resources for both beginner and intermediate data scientists.

  https://www.kdnuggets.com/2020/04/10-must-read-machine-learning-articles-march-2020.html

• Simple Question Answering (QA) Systems That Use Text Similarity Detection in Python

  How exactly are smart algorithms able to engage and communicate with us like humans? The answer lies in Question Answering systems that are built on a foundation of Machine Learning and Natural Language Processing. Let's build one here.

  https://www.kdnuggets.com/2020/04/simple-question-answering-systems-text-similarity-python.html

• A Layman’s Guide to Data Science. Part 2: How to Build a Data Project

  As Part 2 in a Guide to Data Science, we outline the steps to build your first Data Science project, including how to ask good questions to understand the data first, how to prepare the data, how to develop an MVP, reiterate to build a good product, and, finally, present your project.

  https://www.kdnuggets.com/2020/04/guide-data-science-build-data-project.html

• Introduction to Kubeflow MPI Operator and Industry Adoption

  Kubeflow just announced its first major 1.0 release recently. This post introduces the MPI Operator, one of the core components of Kubeflow, currently in alpha, which makes it easy to run synchronized, allreduce-style distributed training on Kubernetes.

  https://www.kdnuggets.com/2020/03/introduction-kubeflow-mpi-operator-industry-adoption.html

• Topic: Coronavirus and COVID-19

  This page features most recent and most important posts on the novel Coronavirus and COVID-19. Here are recent KDnuggets tweets on #Coronavirus Projections COVID-19 Projections Read more »

  https://www.kdnuggets.com/topic/coronavirus

• A Comprehensive Data Repository for Fake Health News Detection

  We introduce the FakeHealth, a new data repository for fake health news detection. Following a preliminary analysis to demonstrate its features, we consider additional potential directions for better identifying fake news.

  https://www.kdnuggets.com/2020/03/data-repository-fake-health-news.html

• Scaling the Wall Between Data Scientist and Data Engineer

  The educational and research focuses of machine learning tends to highlight the model building, training, testing, and optimization aspects of the data science process. To bring these models into use requires a suite of engineering feats and organization, a standard for which does not yet exist. Learn more about a framework for operating a collaborative data science and engineering team to deploy machine learning models to end-users.

  https://www.kdnuggets.com/2020/02/scaling-wall-data-scientist-data-engineer.html

• Using AI to Identify Wildlife in Camera Trap Images from the Serengeti

  With recent developments in machine learning and computer vision, we acquired the tools to provide the biodiversity community with an ability to tap the potential of the knowledge generated automatically with systems triggered by a combination of heat and motion.

  https://www.kdnuggets.com/2020/02/using-ai-identify-wildlife-images-serengeti.html

• Introduction to Geographical Time Series Prediction with Crime Data in R, SQL, and Tableau

  When reviewing geographical data, it can be difficult to prepare the data for an analysis. This article helps by covering importing data into a SQL Server database; cleansing and grouping data into a map grid; adding time data points to the set of grid data and filling in the gaps where no crimes occurred; importing the data into R; running XGBoost model to determine where crimes will occur on a specific day

  https://www.kdnuggets.com/2020/02/introduction-geographical-time-series-crime-r-sql-tableau.html

• Intro to Machine Learning and AI based on high school knowledge

  Machine learning information is becoming pervasive in the media as well as a core skill in new, important job sectors. Getting started in the field can require learning complex concepts, and this article outlines an approach on how to begin learning about these exciting topics based on high school knowledge.

  https://www.kdnuggets.com/2020/02/intro-machine-learning-ai.html

• Past 2020 Meetings / Online Events on AI, Analytics, Big Data, Data Science, and Machine Learning

  Past | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec Read more »

  https://www.kdnuggets.com/meetings/past-meetings-2020.html

• Amazon Gets Into the AutoML Race with AutoGluon: Some AutoML Architectures You Should Know About

  Amazon, Microsoft, Salesforce, Waymo have produced some of the most innovative AutoML architectures in the market.

  https://www.kdnuggets.com/2020/01/amazon-automl-autogluon-architectures-know-about.html

• Exoplanet Hunting Using Machine Learning

  Search for exoplanets — those planets beyond our own solar system — using machine learning, and implement these searches in Python.

  https://www.kdnuggets.com/2020/01/exoplanet-hunting-machine-learning.html

• Top 7 Location Intelligence Companies in 2020

  Here’s a complete list of top 7 location intelligence companies in the market - an overview, pricing, pros, and cons that’ll help you identify the right location intelligence tool for your business.

  https://www.kdnuggets.com/2020/01/top-7-location-intelligence-companies-2020.html

• What Do Data Scientists in Europe Do & How Much Are They Worth?

  Interested in knowing what a data scientist is worth in Europe, and what one does? Read this overview of a recent survey on the topic and gain some insight into the European data science professional job market.

  https://www.kdnuggets.com/2020/01/data-scientist-worth-europe.html

• NLP Year in Review — 2019

  In this blog post, I want to highlight some of the most important stories related to machine learning and NLP that I came across in 2019.

  https://www.kdnuggets.com/2020/01/nlp-year-review-2019.html

• Top 10 Technology Trends for 2020">Top 10 Technology Trends for 2020

  With integrations of multiple emerging technologies just in the past year, AI development continues at a fast pace. Following the blueprint of science and technology advancements in 2019, we predict 10 trends we expect to see in 2020 and beyond.

  https://www.kdnuggets.com/2020/01/top-10-technology-trends-2020.html

• Survey Segmentation Tutorial

  Learn the basics of verifying segmentation, analyzing the data, and creating segments in this tutorial. When reviewing survey data, you will typically be handed Likert questions (e.g., on a scale of 1 to 5), and by using a few techniques, you can verify the quality of the survey and start grouping respondents into populations.

  https://www.kdnuggets.com/2020/01/survey-segmentation-tutorial.html

• Graph Machine Learning Meets UX: An uncharted love affair

  When machine learning tools are developed by technology first, they risk failing to deliver on what users actually need. It can also be difficult for development teams to establish meaningful direction. This article explores the challenges of designing an interface that enables users to visualise and interact with insights from graph machine learning, and explores the very new, uncharted relationship between machine learning and UX.

  https://www.kdnuggets.com/2020/01/graph-machine-learning-ux.html

• 7 Resources to Becoming a Data Engineer">7 Resources to Becoming a Data Engineer

  An estimated 8,650% growth of the volume of Data to 175 zetabytes from 2010 to 2025 has created an enormous need for Data Engineers to build an organization's big data platform to be fast, efficient and scalable.

  https://www.kdnuggets.com/2020/01/resources-become-data-engineer.html

• Automated Machine Learning: How do teams work together on an AutoML project?">Automated Machine Learning: How do teams work together on an AutoML project?

  In this use case, available to the public on GitHub, we’ll see how a data scientist, project manager, and business lead at a retail grocer can leverage automated machine learning and Azure Machine Learning service to reduce product overstock.

  https://www.kdnuggets.com/2020/01/teams-work-together-automl-project.html

• What is Data Catalog and Why You Should Care?

  Learn why data catalogs could be just the thing you need to meet the challenges of data and metadata management and collaboration.

  https://www.kdnuggets.com/2019/12/data-catalog.html

• AI, Analytics, Machine Learning, Data Science, Deep Learning Technology Main Developments in 2019 and Key Trends for 2020">AI, Analytics, Machine Learning, Data Science, Deep Learning Technology Main Developments in 2019 and Key Trends for 2020

  We asked leading experts - what are the most important developments of 2019 and 2020 key trends in AI, Analytics, Machine Learning, Data Science, and Deep Learning? This blog focuses mainly on technology and deployment.

  https://www.kdnuggets.com/2019/12/predictions-ai-machine-learning-data-science-technology.html

• Intro to Grafana: Installation, Configuration, and Building the First Dashboard

  One of the biggest highlights of Grafana is the ability to bring several data sources together in one dashboard with adding rows that will host individual panels. Let's look at installing, configuring, and creating our first dashboard using Grafana.

  https://www.kdnuggets.com/2019/12/intro-grafana-installation-configuration-building-first-dashboard.html

• The 4 Hottest Trends in Data Science for 2020">The 4 Hottest Trends in Data Science for 2020

  The field of Data Science is growing with new capabilities and reach into every industry. With digital transformations occurring in organizations around the world, 2019 included trends of more companies leveraging more data to make better decisions. Check out these next trends in Data Science expected to take off in 2020.

  https://www.kdnuggets.com/2019/12/4-hottest-trends-data-science-2020.html

• AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2019 and Key Trends for 2020">AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2019 and Key Trends for 2020

  As we say goodbye to one year and look forward to another, KDnuggets has once again solicited opinions from numerous research & technology experts as to the most important developments of 2019 and their 2020 key trend predictions.

  https://www.kdnuggets.com/2019/12/predictions-ai-machine-learning-data-science-research.html

• Open Source Projects by Google, Uber and Facebook for Data Science and AI">Open Source Projects by Google, Uber and Facebook for Data Science and AI

  Open source is becoming the standard for sharing and improving technology. Some of the largest organizations in the world namely: Google, Facebook and Uber are open sourcing their own technologies that they use in their workflow to the public.

  https://www.kdnuggets.com/2019/11/open-source-projects-google-uber-facebook-data-science-ai.html

• The Complete Data Science LinkedIn Profile Guide">The Complete Data Science LinkedIn Profile Guide

  With so many Data Scientists showing up on LinkedIn, it's time to make sure your profile is top-notch because your talent is still highly sought after. Recruitment specialists want to find you fast, and this guide will help you create the best profile to feature your expertise.

  https://www.kdnuggets.com/2019/11/data-science-linkedin-profile-guide.html

• Top Machine Learning Software Tools for Developers">Top Machine Learning Software Tools for Developers

  As a developer who is excited about leveraging machine learning for faster and more effective development, these software tools are worth trying out.

  https://www.kdnuggets.com/2019/11/top-machine-learning-software-developers.html

• Artificial Intelligence: Salaries Heading Skyward

  While the average salary for a Software Engineer is around $100,000 to $150,000, to make the big bucks you want to be an AI or Machine Learning (Specialist/Scientist/Engineer.)

  https://www.kdnuggets.com/2019/10/artificial-intelligence-salaries-heading-skyward.html

• Choosing a Machine Learning Model

  Selecting the perfect machine learning model is part art and part science. Learn how to review multiple models and pick the best in both competitive and real-world applications.

  https://www.kdnuggets.com/2019/10/choosing-machine-learning-model.html

• Beyond Word Embedding: Key Ideas in Document Embedding

  This literature review on document embedding techniques thoroughly covers the many ways practitioners develop rich vector representations of text -- from single sentences to entire books.

  https://www.kdnuggets.com/2019/10/beyond-word-embedding-document-embedding.html

• How AI will transform healthcare (and can it fix the US healthcare system?)">How AI will transform healthcare (and can it fix the US healthcare system?)

  This thorough review focuses on the impact of AI, 5G, and edge computing on the healthcare sector in the 2020s as well as a look at quantum computing's potential impact on AI, healthcare, and financial services.

  https://www.kdnuggets.com/2019/09/ai-transform-healthcare.html

• 12 Deep Learning Researchers and Leaders">12 Deep Learning Researchers and Leaders

  Our list of deep learning researchers and industry leaders are the people you should follow to stay current with this wildly expanding field in AI. From early practitioners and established academics to entrepreneurs and today’s top corporate influencers, this diverse group of individuals is leading the way into tomorrow’s deep learning landscape.

  https://www.kdnuggets.com/2019/09/12-deep-learning-research-leaders.html

• My journey path from a Software Engineer to BI Specialist to a Data Scientist">My journey path from a Software Engineer to BI Specialist to a Data Scientist

  The career path of the Data Scientist remains a hot target for many with its continuing high demand. Becoming one requires developing a broad set of skills including statistics, programming, and even business acumen. Learn more about one person's experience making this journey, and discover the many resources available to help you find your way into a world of data science.

  https://www.kdnuggets.com/2019/09/journey-software-engineer-bi-data-scientist.html

• An Overview of Topics Extraction in Python with Latent Dirichlet Allocation

  A recurring subject in NLP is to understand large corpus of texts through topics extraction. Whether you analyze users’ online reviews, products’ descriptions, or text entered in search bars, understanding key topics will always come in handy.

  https://www.kdnuggets.com/2019/09/overview-topics-extraction-python-latent-dirichlet-allocation.html

• Jobs in Data Science, Machine Learning, AI & Analytics

  To add a free short entry here for a job related to Data Science, Machine Learning, AI or Analytics, email the following 5 items to Read more »

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

• Pytorch Cheat Sheet for Beginners and Udacity Deep Learning Nanodegree

  This cheatsheet should be easier to digest than the official documentation and should be a transitional tool to get students and beginners to get started reading documentations soon.

  https://www.kdnuggets.com/2019/08/pytorch-cheat-sheet-beginners.html

• Understanding Tensor Processing Units

  The Tensor Processing Unit (TPU) is Google's custom tool to accelerate machine learning workloads using the TensorFlow framework. Learn more about what TPUs do and how they can work for you.

  https://www.kdnuggets.com/2019/07/understanding-tensor-processing-units.html

• Top 10 Best Podcasts on AI, Analytics, Data Science, Machine Learning">Top 10 Best Podcasts on AI, Analytics, Data Science, Machine Learning

  Check out our latest Top 10 Most Popular Data Science and Machine Learning podcasts available on iTunes. Stay up to date in the field with these recent episodes and join in with the current data conversations.

  https://www.kdnuggets.com/2019/07/best-podcasts-ai-analytics-data-science-machine-learning.html

• Easy, One-Click Jupyter Notebooks

  All of the setup for software, networking, security, and libraries is automatically taken care of by the Saturn Cloud system. Data Scientists can then focus on the actual Data Science and not the tedious infrastructure work that falls around it

  https://www.kdnuggets.com/2019/07/easy-one-click-jupyter-notebooks.html

• 12 Things I Learned During My First Year as a Machine Learning Engineer

  Learn about the day-in-the-life of one machine learning engineer and the important lessons learned for being successful in that role.

  https://www.kdnuggets.com/2019/07/12-things-learned-machine-learning-engineer.html

• XGBoost and Random Forest® with Bayesian Optimisation

  This article will explain how to use XGBoost and Random Forest with Bayesian Optimisation, and will discuss the main pros and cons of these methods.

  https://www.kdnuggets.com/2019/07/xgboost-random-forest-bayesian-optimisation.html

• How Data Science Is Used Within the Film Industry">How Data Science Is Used Within the Film Industry

  As Data Science is becoming pervasive across so many industries, Hollywood is certainly not being left behind. Learn about how Big Data, analytics, and AI are now core drivers of the movies we watch and how we watch them.

  https://www.kdnuggets.com/2019/07/data-science-film-industry.html