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  • Florida Hacks with IBM

    Join the Florida Hacks with IBM virtual hackathon and create a project to tackle sustainability challenges. IBM will provide mentorship and data sets to help bring your ideas to life.

    https://www.kdnuggets.com/2021/08/bemyapp-florida-hacks-ibm.html

  • 15 Python Snippets to Optimize your Data Science Pipeline

    Quick Python solutions to help your data science cycle.

    https://www.kdnuggets.com/2021/08/15-python-snippets-optimize-data-science-pipeline.html

  • What is Noise?

    We might have a reasonable sense for what "noise" is as some statically random phenomena that occurs in Nature. But, how can this same characteristic be defined--and understood--within the context of making judgements, such as in human behavior, corporate decision-making, medicine, the law, and AI systems?

    https://www.kdnuggets.com/2021/08/what-is-noise.html

  • How to Engineer Date Features in Python

    This article discusses and demonstrates how to quickly engineer some common date features using Python.

    https://www.kdnuggets.com/2021/08/engineer-date-features-python.html

  • KDnuggets™ News 21:n32, Aug 25: Open Source Datasets for Computer Vision; Django’s 9 Most Common Applications

    Open Source Datasets for Computer Vision; Django’s 9 Most Common Applications; How to Select an Initial Model for your Data Science Problem; Automate Microsoft Excel and Word Using Python; Stack Overflow Survey Data Science Highlights

    https://www.kdnuggets.com/2021/n32.html

  • Essential Features of An Efficient Data Integration Solution

    This blog highlights the essential features of a data integration solution that help an organization generate consistent and accurate data to keep the business running smoothly.

    https://www.kdnuggets.com/2021/08/essential-features-efficient-data-integration-solution.html

  • Learning Data Science and Machine Learning: First Steps After The Roadmap">Silver BlogLearning Data Science and Machine Learning: First Steps After The Roadmap

    Just getting into learning data science may seem as daunting as (if not more than) trying to land your first job in the field. With so many options and resources online and in traditional academia to consider, these pre-requisites and pre-work are recommended before diving deep into data science and AI/ML.

    https://www.kdnuggets.com/2021/08/learn-data-science-machine-learning.html

  • Top Stories, Aug 16-22: The Difference Between Data Scientists and ML Engineers; Prefect: How to Write and Schedule Your First ETL Pipeline with Python

    Also: Open Source Datasets for Computer Vision; Prefect: How to Write and Schedule Your First ETL Pipeline with Python; Most Common Data Science Interview Questions and Answers; How to Select an Initial Model for your Data Science Problem.

    https://www.kdnuggets.com/2021/08/top-news-week-0816-0822.html

  • Jurassic-1 Language Models and AI21 Studio

    AI21 Labs’ new developer platform offers instant access to our 178B-parameter language model, to help you build sophisticated text-based AI applications at scale.

    https://www.kdnuggets.com/2021/08/ai21-jurassic1-language-models.html

  • Django’s 9 Most Common Applications">Gold BlogDjango’s 9 Most Common Applications

    Django is a Python web application framework enjoying widespread adoption in the data science community. But what else can you use Django for? Read this article for 9 use cases where you can put Django to work.

    https://www.kdnuggets.com/2021/08/django-9-common-applications.html

  • 7 reasons you should get a formal degree in Data Science

    So many options are now available online to learn in the field of data science. There are several factors to consider to determine if these options or a traditional degree from an academic institution is the best approach for your personal learning style and career aspirations.

    https://www.kdnuggets.com/2021/08/7-reasons-degree-data-science.html

  • 5 Things That Make My Job as a Data Scientist Easier

    After working as a Data Scientist for a year, I am here to share some things I learnt along the way that I feel are helpful and have increased my efficiency. Hopefully some of these tips can help you in your journey :)

    https://www.kdnuggets.com/2021/08/5-things-job-data-scientist-easier.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

  • Demystifying AI: The prejudices of Artificial Intelligence (and human beings)

    AI models are necessarily trained on historical data from the real-world--data that is generated from the daily goings on of society. If social-based biases are inherent in the training data, then will the AI predictions highlight these same biases? If so, what should we do (or not do) about making AI fair?

    https://www.kdnuggets.com/2021/08/demystifying-ai-prejudices.html

  • How to Select an Initial Model for your Data Science Problem

    Save yourself some time and headaches and start simple.

    https://www.kdnuggets.com/2021/08/select-initial-model-data-science-problem.html

  • Speeding up data understanding by interactive exploration

    A key success factor of data science projects is to understand the data well. This blog explains why coding can be inefficient for this and how you can improve.

    https://www.kdnuggets.com/2021/08/visplore-data-understanding-interactive-exploration.html

  • 5 Data Science Career Mistakes To Avoid

    Everyone makes mistakes, which can be a good thing when they lead to learning and improvements over time. But, we can also try to first learn from others to expedite our personal growth. To get started, consider these lessons learned the hard way, so you don’t have to.

    https://www.kdnuggets.com/2021/08/5-data-science-career-mistakes-avoid.html

  • Enhancing Machine Learning Personalization through Variety

    Personalization drives growth and is a touchstone of good customer experience. Personalization driven through machine learning can enable companies to improve this experience while improving ROI for marketing campaigns. However, challenges exist in these techniques for when personalization makes sense and how and when specific options are recommended.

    https://www.kdnuggets.com/2021/08/machine-learning-personalization-variety.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

  • When Correlation is Better than Causation

    Identifying causality in an analysis isn't always practical. We show a heuristic approach for using correlations to inform decisions.

    https://www.kdnuggets.com/2021/08/correlation-better-causation.html

  • Open Source Datasets for Computer Vision">Silver BlogOpen Source Datasets for Computer Vision

    Access to high-quality, noise-free, large-scale datasets is crucial for training complex deep neural network models for computer vision applications. Many open-source datasets are developed for use in image classification, pose estimation, image captioning, autonomous driving, and object segmentation. These datasets must be paired with the appropriate hardware and benchmarking strategies to optimize performance.

    https://www.kdnuggets.com/2021/08/open-source-datasets-computer-vision.html

  • Data Scientist’s Guide to Efficient Coding in Python

    Read this fantastic collection of tips and tricks the author uses for writing clean code on a day-to-day basis.

    https://www.kdnuggets.com/2021/08/data-scientist-guide-efficient-coding-python.html

  • KDnuggets™ News 21:n31, Aug 18: The Difference Between Data Scientists and ML Engineers; MLOPs And Machine Learning RoadMap

    What is the difference between Data Scientists and ML Engineers? How does MLOPs fit into Machine Learning RoadMap? How to Train a BERT Model From Scratch? What is so great about Intro to Statistical Learning, 2nd Edition? Find the answers to these questions and more in this issue.

    https://www.kdnuggets.com/2021/n31.html

  • Top July Stories: Data Scientists and ML Engineers Are Luxury Employees

    Also: Top 6 Data Science Online Courses in 2021; Advice for Learning Data Science from Google's Director of Research; 5 Lessons McKinsey Taught Me That Will Make You a Better Data Scientist

    https://www.kdnuggets.com/2021/08/top-stories-2021-jul.html

  • Leaders at Allstate, eBay & Red Bull Agree: Don’t Miss the Rev 3 Enterprise MLOps Summit

    Join data science and MLOps leaders in-person in Chicago this November.

    https://www.kdnuggets.com/2021/08/domino-rev3-enterprise-mlops-summit.html

  • Linear Algebra for Natural Language Processing

    Learn about representing word semantics in vector space.

    https://www.kdnuggets.com/2021/08/linear-algebra-natural-language-processing.html

  • Model Drift in Machine Learning – How To Handle It In Big Data

    Rendezvous Architecture helps you run and choose outputs from a Champion model and many Challenger models running in parallel without many overheads. The original approach works well for smaller data sets, so how can this idea adapt to big data pipelines?

    https://www.kdnuggets.com/2021/08/model-drift-machine-learning-big-data.html

  • What I Learned From “Women in Data Science” Conferences

    Read the author's perspective after attending 3 "Women in Data Science" conferences.

    https://www.kdnuggets.com/2021/08/learned-women-data-science-conferences.html

  • Top Stories, Aug 9-15: The Difference Between Data Scientists and ML Engineers

    Also: Most Common Data Science Interview Questions and Answers; 3 Reasons Why You Should Use Linear Regression Models Instead of Neural Networks; How My Learning Path Changed After Becoming a Data Scientist; MLOPs And Machine Learning RoadMap

    https://www.kdnuggets.com/2021/08/top-news-week-0809-0815.html

  • KDnuggets Top Blogs Rewards for July 2021

    These top blogs were winners of KDnuggets Top Blog Rewards Program for July: Data Scientists and ML Engineers Are Luxury Employees; Top 6 Data Science Online Courses in 2021; Advice for Learning Data Science from Google's Director of Research; Pandas not enough? Here are a few good alternatives; A Learning Path To Becoming a Data Scientist; 5 Lessons McKinsey Taught Me That Will Make You a Better Data Scientist

    https://www.kdnuggets.com/2021/08/top-blogs-rewards-jul.html

  • Prefect: How to Write and Schedule Your First ETL Pipeline with Python">Gold BlogPrefect: How to Write and Schedule Your First ETL Pipeline with Python

    Workflow management systems made easy — both locally and in the cloud.

    https://www.kdnuggets.com/2021/08/prefect-write-schedule-etl-pipeline-python.html

  • Agile Data Labeling: What it is and why you need it

    The notion of Agile in software development has made waves across industries with its revolution for productivity. Can the same benefits be applied to the often arduous task of annotating data sets for machine learning?

    https://www.kdnuggets.com/2021/08/agile-data-labeling.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

  • How to Train a BERT Model From Scratch

    Meet BERT’s Italian cousin, FiliBERTo.

    https://www.kdnuggets.com/2021/08/train-bert-model-scratch.html

  • Querying the Most Granular Demographics Dataset

    Having access to broad and detailed population data can potentially offer enormous value to any organization looking to interact with specific demographics. However, access alone is not sufficient without being able to leverage advanced techniques to explore and visualize the data.

    https://www.kdnuggets.com/2021/08/querying-granular-demographic-dataset.html

  • Introduction to Statistical Learning Second Edition

    The second edition of the classic "An Introduction to Statistical Learning, with Applications in R" was published very recently, and is now freely-available via PDF on the book's website.

    https://www.kdnuggets.com/2021/08/introduction-statistical-learning-v2.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

  • 3 mindset changes to become a better analyst

    Once fresh out of school and ready to burst into an organization as a new hire with newly-developed skills and knowledge, many have learned that things tend to be a little different in the "real world" compared to university. A few shifts in your approach to continued learning and expanding your confidence might help you professionally reach a little further, faster.

    https://www.kdnuggets.com/2021/08/3-mindset-changes-better-analyst.html

  • How to Detect and Overcome Model Drift in MLOps

    This article has a look at model drift, and how to detect and overcome it in production MLOps.

    https://www.kdnuggets.com/2021/08/detect-overcome-model-drift-mlops.html

  • 2021 State of Production Machine Learning Survey

    We invite you to take the 2021 State of Production Machine Learning survey and help shed light on the latest trends in the adoption of machine learning (ML) in the industry. 

    https://www.kdnuggets.com/2021/08/anyscale-2021-state-production-machine-learning-survey.html

  • Platinum BlogThe Difference Between Data Scientists and ML Engineers">Rewards BlogPlatinum BlogThe Difference Between Data Scientists and ML Engineers

    What's the difference? Responsibilities, expertise, and salary expectations.

    https://www.kdnuggets.com/2021/08/difference-between-data-scientists-ml-engineers.html

  • For SQL, or why I’m so over-protective of my data people

    For decades, SQL has been the foundation for how humans interact with data. Alternate approaches seem to continually attempt to replace this powerful language. However, while much progress remains in the techniques and tools for the curation and management of data, the skilled craftspeople who work with data -- through the lens of SQL -- are likely to be around for decades more.

    https://www.kdnuggets.com/2021/08/for-sql-data-people.html

  • DeepMind’s New Super Model: Perceiver IO is a Transformer that can Handle Any Dataset

    The new transformer-based architecture can process audio, video and images using a single model.

    https://www.kdnuggets.com/2021/08/deepmind-new-super-model-perceiver-io-transformer.html

  • KDnuggets™ News 21:n30, Aug 11: Most Common Data Science Interview Questions and Answers; How Visualization is Transforming Exploratory Data Analysis

    Most Common Data Science Interview Questions and Answers; How Visualization is Transforming Exploratory Data Analysis; How To Become A Freelance Data Scientist – 4 Practical Tips; How to Query Your Pandas Dataframe; Essential Math for Data Science: Introduction to Systems of Linear Equations

    https://www.kdnuggets.com/2021/n30.html

  • AI in Real Life

    What do you need to get started on your AI journey? Putting together a combination of the right project, people and infrastructure is no easy task. SAS and MIT SMR have collaborated to provide a comprehensive set of resources to guide you from conception to implementation. Learn from experts that successfully launched AI projects.

    https://www.kdnuggets.com/2021/08/sas-ai-real-life.html

  • How My Learning Path Changed After Becoming a Data Scientist

    I keep learning but in a different way.

    https://www.kdnuggets.com/2021/08/learning-path-changed-becoming-data-scientist.html

  • Practising SQL without your own database">Silver BlogPractising SQL without your own database

    SQL is a very important skill for data analysts and data scientists. However, when you are just starting out learning in the field, how can you practice querying with SQL if you don’t have any data stored in a database?

    https://www.kdnuggets.com/2021/08/sql-without-own-database.html

  • Visualizing Bias-Variance

    In this article, we'll explore some different perspectives of what the bias-variance trade-off really means with the help of visualizations.

    https://www.kdnuggets.com/2021/08/visualizing-bias-variance.html

  • 5 Tips for Writing Clean R Code

    This article summarizes the most common mistakes to avoid and outline best practices to follow in programming in general. Follow these tips to speed up the code review iteration process and be a rockstar developer in your reviewer’s eyes!

    https://www.kdnuggets.com/2021/08/5-tips-writing-clean-r-code.html

  • Top Stories, Aug 2-8: 3 Reasons Why You Should Use Linear Regression Models Instead of Neural Networks; Bootstrap a Modern Data Stack in 5 minutes with Terraform

    Also: Most Common Data Science Interview Questions and Answers; How Visualization is Transforming Exploratory Data Analysis; GitHub Copilot Open Source Alternatives; How To Become A Freelance Data Scientist – 4 Practical Tips

    https://www.kdnuggets.com/2021/08/top-news-week-0802-0808.html

  • Including ModelOps in your AI strategy

    The strategic power of AI has been established thoroughly across many industries and companies, leading to surges in model creation. Investments in the people, processes, and tools for operationalizing models, referred to as ModelOps, lag. This function of operationalizing, integrating, and deploying AI models in line with businesses value expectations is growing into a core business capability as global use of AI matures.

    https://www.kdnuggets.com/2021/08/modelops-ai-strategy.html

  • How to Query Your Pandas Dataframe">Gold BlogHow to Query Your Pandas Dataframe

    A Data Scientist’s perspective on SQL-like Python functions.

    https://www.kdnuggets.com/2021/08/query-pandas-dataframe.html

  • Using Twitter to Understand Pizza Delivery Apprehension During COVID

    Analyzing customer sentiments and capturing any specific difference in emotion to order Dominos pizza in India during lockdown.

    https://www.kdnuggets.com/2021/08/twitter-understand-pizza-delivery-covid.html

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

  • Essential Math for Data Science: Introduction to Systems of Linear Equations

    In this post, you’ll see how you can use systems of equations and linear algebra to solve a linear regression problem.

    https://www.kdnuggets.com/2021/08/essential-math-data-science-introduction-systems-linear-equations.html

  • Be Wary of Automated Feature Selection — Chi Square Test of Independence Example

    When Data Scientists use chi square test for feature selection, they just merely go by the ritualistic “If your p-value is low, the null hypothesis must go”. The automated function they use behaves no differently.

    https://www.kdnuggets.com/2021/08/automated-feature-selection-chi-square-test-independence-example.html

  • Gold BlogMost Common Data Science Interview Questions and Answers">Rewards BlogGold BlogMost Common Data Science Interview Questions and Answers

    After analyzing 900+ data science interview questions from companies over the past few years, the most common data science interview question categories are reviewed in this guide, each explained with an example.

    https://www.kdnuggets.com/2021/08/common-data-science-interview-questions-answers.html

  • Artificial Intelligence vs Machine Learning in Cybersecurity

    Artificial Intelligence and Machine Learning are the next-gen technology used in various fields. With the rise in online threats, it has become essential to include these technologies in cybersecurity. In this post, we will know what roles do AI and ML play in cybersecurity.

    https://www.kdnuggets.com/2021/08/artificial-intelligence-machine-learning-cybersecurity.html

  • How Visualization is Transforming Exploratory Data Analysis">Silver BlogHow Visualization is Transforming Exploratory Data Analysis

    Data analysts are dealing with bigger datasets than ever before, making interrogation difficult. Visualized Exploratory Data Analysis, supported by advanced parallel computing, promises an answer.

    https://www.kdnuggets.com/2021/08/visualization-transforming-exploratory-data-analysis.html

  • How To Become A Freelance Data Scientist – 4 Practical Tips">Silver BlogHow To Become A Freelance Data Scientist – 4 Practical Tips

    If you are a nerd-ish data scientist who wants to start working as an independent (remote) freelance data scientist, then these four practical tips can help you transition from the traditional 9-to-5 job to a dynamic experience as a remote contractor, just as the author did three years ago.

    https://www.kdnuggets.com/2021/08/how-become-freelance-data-scientist.html

  • How DeepMind Trains Agents to Play Any Game Without Intervention

    A new paper proposes a new architecture and training environment for generally capable agents.

    https://www.kdnuggets.com/2021/08/deepmind-trains-agents-play-without-intervention.html

  • KDnuggets™ News 21:n29, Aug 4: GitHub Copilot Open Source Alternatives; 3 Reasons Why You Should Use Linear Regression Models Instead of Neural Networks

    GitHub Copilot Open Source Alternatives; 3 Reasons Why You Should Use Linear Regression Models Instead of Neural Networks; A Brief Introduction to the Concept of Data; MLOps Best Practices; GPU-Powered Data Science (NOT Deep Learning) with RAPIDS

    https://www.kdnuggets.com/2021/n29.html

  • Free dataset worth $1350 to test the accent gap!

    With so many accent variations, how do speech and voice technologies keep up? In a few words: accented speech training data, representative of diverse groups of people. The more people your model can understand, the more likely you are to acquire and retain customers.

    https://www.kdnuggets.com/2021/08/definedcrowd-free-dataset-accent-gap.html

  • Mastering Clustering with a Segmentation Problem

    The one stop shop for implementing the most widely used models in Python for unsupervised clustering.

    https://www.kdnuggets.com/2021/08/mastering-clustering-segmentation-problem.html

  • 30 Most Asked Machine Learning Questions Answered

    There is always a lot to learn in machine learning. Whether you are new to the field or a seasoned practitioner and ready for a refresher, understanding these key concepts will keep your skills honed in the right direction.

    https://www.kdnuggets.com/2021/08/30-machine-learning-questions-answered.html

  • How To 2x Your Data Analytics Consulting Rates (Overnight)

    Looking to up your data analytics consulting rates? Learn exactly what most freelancers are charging, and the rates you SHOULD be charging as a business intelligence and analytics consultant. This post will show you what you need to know to achieve maximum results for your data consulting career.

    https://www.kdnuggets.com/2021/08/2x-data-analytics-consulting-rates-overnight.html

  • GPU-Powered Data Science (NOT Deep Learning) with RAPIDS">Gold BlogGPU-Powered Data Science (NOT Deep Learning) with RAPIDS

    How to utilize the power of your GPU for regular data science and machine learning even if you do not do a lot of deep learning work.

    https://www.kdnuggets.com/2021/08/gpu-powered-data-science-deep-learning-rapids.html

  • Top Stories, Jul 26 – Aug 1: GitHub Copilot Open Source Alternatives; Why and how should you learn “Productive Data Science”?

    Also: Advice for Learning Data Science from Google’s Director of Research; Design patterns in machine learning; A Brief Introduction to the Concept of Data; 5 Mistakes I Wish I Had Avoided in My Data Science Career

    https://www.kdnuggets.com/2021/08/top-news-week-0726-0801.html

  • Gold Blog3 Reasons Why You Should Use Linear Regression Models Instead of Neural Networks">Rewards BlogGold Blog3 Reasons Why You Should Use Linear Regression Models Instead of Neural Networks

    While there may always seem to be something new, cool, and shiny in the field of AI/ML, classic statistical methods that leverage machine learning techniques remain powerful and practical for solving many real-world business problems.

    https://www.kdnuggets.com/2021/08/3-reasons-linear-regression-instead-neural-networks.html

  • Development & Testing of ETL Pipelines for AWS Locally

    Typically, development and testing ETL pipelines is done on real environment/clusters which is time consuming to setup & requires maintenance. This article focuses on the development and testing of ETL pipelines locally with the help of Docker & LocalStack. The solution gives flexibility to test in a local environment without setting up any services on the cloud.

    https://www.kdnuggets.com/2021/08/development-testing-etl-pipelines-aws-locally.html

  • Towards a Responsible and Ethical AI

    It is not the technology at fault, but the intention.

    https://www.kdnuggets.com/2021/07/towards-responsible-ethical-ai.html

  • Data Monetization 101

    The evolving marketplace of data now includes many firms that support a variety of needs from organizations looking to grow with data. This listing of the key players categorized by target market provides an interesting picture of this exciting industry sector.

    https://www.kdnuggets.com/2021/07/data-monetization-101.html

  • 10 Machine Learning Model Training Mistakes

    These common ML model training mistakes are easy to overlook but costly to redeem.

    https://www.kdnuggets.com/2021/07/10-machine-learning-model-training-mistakes.html

  • Online Master’s in Data Science from Northwestern

    Build statistical and analytical expertise as well as the management and leadership skills necessary to implement high-level, data-driven decisions in Northwestern's online Master of Science in Data Science program. Apply now!

    https://www.kdnuggets.com/2021/07/northwestern-online-ms-data-science.html

  • GitHub Copilot Open Source Alternatives">Gold BlogGitHub Copilot Open Source Alternatives

    GitHub's Copilot code generation tool is currently only available via approved request. Here are 4 Copilot alternatives that you can use in your programming today.

    https://www.kdnuggets.com/2021/07/github-copilot-open-source-alternatives-code-generation.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

  • A Brief Introduction to the Concept of Data">Silver BlogA Brief Introduction to the Concept of Data

    Every aspiring data scientist must know the concept of data and the kind of analysis they can run. This article introduces the concept of data (quantitative and qualitative) and the types of analysis.

    https://www.kdnuggets.com/2021/07/brief-introduction-concept-data.html

  • An AI-Based Framework Solution to Address Email Management Challenges

    Expert.ai’s Edge NL API is an on-premise API that can perform NLU tasks with no required training or extra work, offering advanced, out-of-the-box capabilities that address common use cases and can be easily customized to your specific needs.

    https://www.kdnuggets.com/2021/07/expertai-ai-based-framework-solution-email-management.html

  • The Brutal Truth About Data Science

    Many organizations approach data science as though it was a marketing tool — relabeling things that they already do as ‘data science’ as it involves the use of data. That is not real data science, and it completely misses the point of engaging in data science.

    https://www.kdnuggets.com/2021/07/brutal-truth-data-science.html

  • dbt for Data Transformation – Hands-on Tutorial

    The data build tool (dbt) is gaining in popularity and use, and this hands-on tutorial covers creating complex models, using variables and functions, running tests, generating docs, and many more features.

    https://www.kdnuggets.com/2021/07/dbt-data-transformation-tutorial.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

  • KDnuggets™ News 21:n28, Jul 28: Design patterns in machine learning; The Best NLP Course is Free

    What are the Design patterns for Machine Learning and why you should know them? For more advanced readers, how to use Kafka Connect to create an open source data pipeline for processing real-time data; The state-of-the-art NLP course is freely available; Python Data Structures Compared; Update your Machine Learning skills this summer.

    https://www.kdnuggets.com/2021/n28.html

  • ARTIFICIAL INTELLIGENCE (AI), A TEXTBOOK

    This book covers the broader field of AI, carefully balancing coverage between classical AI (logic or deductive reasoning) and modern AI (inductive learning and neural networks).

    https://www.kdnuggets.com/2021/07/charu-ai-textbook.html

  • Python Data Structures Compared

    Let's take a look at 5 different Python data structures and see how they could be used to store data we might be processing in our everyday tasks, as well as the relative memory they use for storage and time they take to create and access.

    https://www.kdnuggets.com/2021/07/python-data-structures-compared.html

  • Machine Learning Skills – Update Yours This Summer

    The process of mastering new knowledge often requires multiple passes to ensure the information is deeply understood. If you already began your journey into machine learning and data science, then you are likely ready for a refresher on topics you previously covered. This eight-week self-learning path will help you recapture the foundations and prepare you for future success in applying these skills.

    https://www.kdnuggets.com/2021/07/update-your-machine-learning-skills.html

  • Facebook Open Sources a Chatbot That Can Discuss Any Topic

    The new version expands the capabilities of its predecessor building a much more natural conversational experience.

    https://www.kdnuggets.com/2021/07/facebook-open-sources-chatbot-discuss-any-topic.html

  • Top Stories, Jul 19-25: Top 6 Data Science Online Courses in 2021; 11 Important Probability Distributions Explained

    Also: Google’s Director of Research Advice for Learning Data Science; Geometric foundations of Deep Learning; How Can You Distinguish Yourself from Hundreds of Other Data Science Candidates?; Design patterns in machine learning

    https://www.kdnuggets.com/2021/07/top-news-week-0719-0725.html

  • Not Only for Deep Learning: How GPUs Accelerate Data Science & Data Analytics">Gold BlogNot Only for Deep Learning: How GPUs Accelerate Data Science & Data Analytics

    Modern AI/ML systems’ success has been critically dependent on their ability to process massive amounts of raw data in a parallel fashion using task-optimized hardware. Can we leverage the power of GPU and distributed computing for regular data processing jobs too?

    https://www.kdnuggets.com/2021/07/deep-learning-gpu-accelerate-data-science-data-analytics.html

  • 5 Mistakes I Wish I Had Avoided in My Data Science Career

    Everyone makes mistakes, which can be a good thing when they lead to learning and improvements over time. But, we can also try to first learn from others to expedite our personal growth. To get started, consider these lessons learned the hard way, so you don’t have to.

    https://www.kdnuggets.com/2021/07/5-mistakes-data-science-career.html

  • Why and how should you learn “Productive Data Science”?">Gold BlogWhy and how should you learn “Productive Data Science”?

    What is Productive Data Science and what are some of its components?

    https://www.kdnuggets.com/2021/07/learn-productive-data-science.html

  • Top Python Data Science Interview Questions

    Six must-know technical concepts and two types of questions to test them.

    https://www.kdnuggets.com/2021/07/top-python-data-science-interview-questions.html

  • Full cross-validation and generating learning curves for time-series models

    Standard cross-validation on time series data is not possible because the data model is sequential, which does not lend well to splitting the data into statistically useful training and validation sets. However, a new approach called Reconstructive Cross-validation may pave the way toward performing this type of important analysis for predictive models with temporal datasets.

    https://www.kdnuggets.com/2021/07/full-cross-validation-learning-curves-time-series.html

  • How to Use Kafka Connect to Create an Open Source Data Pipeline for Processing Real-Time Data

    This article shows you how to create a real-time data pipeline using only pure open source technologies. These include Kafka Connect, Apache Kafka, Kibana and more.

    https://www.kdnuggets.com/2021/07/kafka-open-source-data-pipeline-processing-real-time-data.html

  • Overview of Albumentations: Open-source library for advanced image augmentations

    With code snippets on augmentations and integrations with PyTorch and Tensorflow pipelines.

    https://www.kdnuggets.com/2021/07/overview-albumentations-open-source-library-advanced-image-augmentations.html

  • The Lost Art of Decile Analysis

    The goal of classification is a primary and widely-used application of machine learning algorithms. However, if careful consideration through additional analysis is not taken into the subtlety in the results of an even an apparently straightforward binary classifier, then the deeper meaning of your prediction may be obscured.

    https://www.kdnuggets.com/2021/07/lost-art-decile-analysis.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

  • MS in Analytics at Northwestern – Learn about the benefits of corporate sponsorship

    The MS in Analytics program at Northwestern invites you to an info session about project sponsorship, Aug 3 at 5 pm CT. Discover how your business can benefit from actionable machine learning solutions and insights developed by Northwestern students.

    https://www.kdnuggets.com/2021/07/northwestern-ms-analytics-partner.html

  • The Best SOTA NLP Course is Free!

    Hugging Face has recently released a course on using its libraries and ecosystem for practical NLP, and it appears to be very comprehensive. Have a look for yourself.

    https://www.kdnuggets.com/2021/07/best-sota-nlp-course-free.html

  • WHT: A Simpler Version of the fast Fourier Transform (FFT) you should know

    The fast Walsh Hadamard transform is a simple and useful algorithm for machine learning that was popular in the 1960s and early 1970s. This useful approach should be more widely appreciated and applied for its efficiency.

    https://www.kdnuggets.com/2021/07/wht-simpler-fast-fourier-transform-fft.html

  • Design patterns in machine learning">Silver BlogDesign patterns in machine learning

    Can we abstract best practices to real design patterns yet?

    https://www.kdnuggets.com/2021/07/design-patterns-machine-learning.html

  • KDnuggets™ News 21:n27, Jul 21: Top 6 Data Science Online Courses in 2021; Geometric Foundations of Deep Learning

    Top 6 Data Science Online Courses in 2021; Geometric foundations of Deep Learning; Google’s Director of Research Advice for Learning Data Science; SQL, Syllogisms, and Explanations; How to Create Unbiased Machine Learning Models

    https://www.kdnuggets.com/2021/n27.html

  • When to Retrain an Machine Learning Model? Run these 5 checks to decide on the schedule

    Machine learning models degrade with time, and need to be regularly updated. In the article, we suggest how to approach retraining and plan for it in advance.

    https://www.kdnuggets.com/2021/07/retrain-machine-learning-model-5-checks-decide-schedule.html

  • 11 Important Probability Distributions Explained">Gold Blog11 Important Probability Distributions Explained

    There are many distribution functions considered in statistics and machine learning, which can seem daunting to understand at first. Many are actually closely related, and with these intuitive explanations of the most important probability distributions, you can begin to appreciate the observations of data these distributions communicate.

    https://www.kdnuggets.com/2021/07/11-important-probability-distributions-explained.html

  • Understanding BERT with Hugging Face

    We don’t really understand something before we implement it ourselves. So in this post, we will implement a Question Answering Neural Network using BERT and a Hugging Face Library.

    https://www.kdnuggets.com/2021/07/understanding-bert-hugging-face.html

  • Top Stories, Jul 12-18: Top 6 Data Science Online Courses in 2021; Become an Analytics Engineer in 90 Days

    Also: Data Scientists and ML Engineers Are Luxury Employees; Geometric foundations of Deep Learning; How Can You Distinguish Yourself from Hundreds of Other Data Science Candidates?; A Learning Path To Becoming a Data Scientist

    https://www.kdnuggets.com/2021/07/top-news-week-0712-0718.html

  • How Much Memory is your Machine Learning Code Consuming?

    Learn how to quickly check the memory footprint of your machine learning function/module with one line of command. Generate a nice report too.

    https://www.kdnuggets.com/2021/07/memory-machine-learning-code-consuming.html

  • Silver BlogAdvice for Learning Data Science from Google’s Director of Research">Rewards BlogSilver BlogAdvice for Learning Data Science from Google’s Director of Research

    Surfing the professional career wave in data science is a hot prospect for many looking to get their start in the world. The digital revolution continues to create many exciting new opportunities. But, jumping in too fast without fully establishing your foundational skills can be detrimental to your success, as is suggested by this advice for data science newbies from Peter Norvig, the Director of Research at Google.

    https://www.kdnuggets.com/2021/07/google-advice-learning-data-science.html

  • Why Saying “We Accept the Null Hypothesis” is Wrong: An Intuitive Explanation

    “The opposite of ‘Rejecting the Null’ is ‘Accepting’ isn’t it?”. Well, it is not so simple as it is construed. We need to rise above antonyms and understand one crucial concept.

    https://www.kdnuggets.com/2021/07/accept-null-hypothesis-wrong-intuitive-explanation.html

  • How to Create Unbiased Machine Learning Models

    In this post we discuss the concepts of bias and fairness in the Machine Learning world, and show how ML biases often reflect existing biases in society. Additionally, We discuss various methods for testing and enforcing fairness in ML models.

    https://www.kdnuggets.com/2021/07/create-unbiased-machine-learning-models.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

  • Pushing No-Code Machine Learning to the Edge

    Discover the power of no-code machine learning, and what it can accomplish when pushed to edge devices.

    https://www.kdnuggets.com/2021/07/pushing-no-code-machine-learning-edge.html

  • AWS Webinar: How are data-driven companies using ESG and sustainability data to make actionable decisions?

    In this virtual session, on Jul 29 @ 11AM PT, 2PM ET, our panel of experts will uncover how companies across several verticals use ESG data to move beyond the reporting benchmark, deepen business insights, and create competitive differentiation.

    https://www.kdnuggets.com/2021/07/roidna-aws-webinar-data-driven-esg-sustainability-decisions.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

  • Platinum BlogTop 6 Data Science Online Courses in 2021">Rewards BlogPlatinum BlogTop 6 Data Science Online Courses in 2021

    As an aspiring data scientist, it is easy to get overwhelmed by the abundance of resources available on the Internet. With these 6 online courses, you can develop yourself from a novice to experienced in less than a year, and prepare you with the skills necessary to land a job in data science.

    https://www.kdnuggets.com/2021/07/top-6-data-science-online-courses.html

  • Date Processing and Feature Engineering in Python

    Have a look at some code to streamline the parsing and processing of dates in Python, including the engineering of some useful and common features.

    https://www.kdnuggets.com/2021/07/date-pre-processing-feature-engineering-python.html

  • Shareable data analyses using templates

    We've been using shared data analyses in production for three years. Here's how you can create reusable templates for common metrics and analyses.

    https://www.kdnuggets.com/2021/07/shareable-data-analyses-using-templates.html

  • Geometric foundations of Deep Learning">Gold BlogGeometric foundations of Deep Learning

    Geometric Deep Learning is an attempt for geometric unification of a broad class of machine learning problems from the perspectives of symmetry and invariance. These principles not only underlie the breakthrough performance of convolutional neural networks and the recent success of graph neural networks but also provide a principled way to construct new types of problem-specific inductive biases.

    https://www.kdnuggets.com/2021/07/geometric-foundations-deep-learning.html

  • SQL, Syllogisms, and Explanations

    Check out the Executable English Platform, for self-explaining applications written in English that you can run in your browser.

    https://www.kdnuggets.com/2021/07/sql-syllogisms-explanations.html

  • KDnuggets™ News 21:n26, Jul 14: Pandas not enough? Here are a few good alternatives to processing larger and faster data in Python; 5 Python Data Processing Tips

    If Pandas not enough, here are a few good alternatives to processing larger and faster data in Python; 5 Python Data Processing Tips and Code Snippets; Relax! Data Scientists will not go extinct in 10 years, but the role will change; How to Get Practical Data Science Experience to be Career-Ready.

    https://www.kdnuggets.com/2021/n26.html

  • Top June Stories: 5 Tasks To Automate With Python; Data Scientists Will be Extinct in 10 Years

    5 Tasks To Automate With Python; Data Scientists Will be Extinct in 10 Years: How to Generate Automated PDF Documents with Python; How I Doubled My Income with Data Science and Machine Learning.

    https://www.kdnuggets.com/2021/07/top-stories-2021-jun.html

  • Building Tech Skills in 2021

    With all the workforce changes last year, it is not surprising that employees lack the skills to meet new demands. To be ready for today’s challenges, companies need sound methods to assess what skills their employees have, the ability to identify the gaps, and a plan to upskill them for success. You can read the survey results here, along with predicted learning and development trends, and insights for upskilling, cross-skilling and reskilling your workforce.

    https://www.kdnuggets.com/2021/07/sas-building-tech-skills.html

  • Streamlit Tips, Tricks, and Hacks for Data Scientists

    Today, I am going to talk about a few tips that I learned within more than a year of using Streamlit, that you can also use to unleash your powerful DS/AI/ML (whatever they may be) applications.

    https://www.kdnuggets.com/2021/07/streamlit-tips-tricks-hacks-data-scientists.html

  • AGI and the Future of Humanity

    The possibilities for humanity's future very likely includes at least one in which computers will exceed human abilities. Artificial General Intelligence (AGI) does not necessarily have to be all doom and gloom. However, we must begin now to understand how this technical evolution might progress and consider what actions to take now to prepare.

    https://www.kdnuggets.com/2021/07/agi-future-humanity.html

  • How Can You Distinguish Yourself from Hundreds of Other Data Science Candidates?">Silver BlogHow Can You Distinguish Yourself from Hundreds of Other Data Science Candidates?

    A few easy (and not-so-easy) ways to prove to employers that your skills and attitudes place you in a higher bracket.

    https://www.kdnuggets.com/2021/07/distinguish-yourself-hundreds-other-data-science-candidates.html

  • Top Stories, Jul 5-11: Data Scientists and ML Engineers Are Luxury Employees

    Also: Pandas not enough? Here are a few good alternatives to processing larger and faster data in Python; A Learning Path To Becoming a Data Scientist; 5 Lessons McKinsey Taught Me That Will Make You a Better Data Scientist; 5 Python Data Processing Tips & Code Snippets

    https://www.kdnuggets.com/2021/07/top-news-week-0705-0711.html

  • KDnuggets Top Blogs Rewards for June 2021

    These top blogs were winners of KDnuggets Top Blog Rewards Program for June: 5 Tasks To Automate With Python; Data Scientists Will be Extinct in 10 Years; How to Generate Automated PDF Documents with Python; How I Doubled My Income with Data Science and Machine Learning; Pandas vs SQL: When Data Scientists Should Use Each Tool; Top 10 Data Science Projects for Beginners.

    https://www.kdnuggets.com/2021/07/top-blogs-rewards-jun.html

  • Abstraction and Data Science: Not a great combination

    The article is about too much abstraction and how this programming concept when extended to Data Science makes Data Science non-intuitive.

    https://www.kdnuggets.com/2021/07/abstraction-data-science-not-great-combination.html

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

  • How to Tell if You Have Trained Your Model with Enough Data

    WeightWatcher is an open-source, diagnostic tool for evaluating the performance of (pre)-trained and fine-tuned Deep Neural Networks. It is based on state-of-the-art research into Why Deep Learning Works.

    https://www.kdnuggets.com/2021/07/tell-model-trained-enough-data.html

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