Search results for Advanced Analytics

Found 740 documents, 5944 searched:

• How to Create a Dataset for Machine Learning

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

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

• The Challenges of Being a Data Scientist

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

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

• The Challenges of Creating Features for Machine Learning

  What are the challenges of creating features for machine learning and how can we mitigate them.

  https://www.kdnuggets.com/2022/02/challenges-creating-features-machine-learning.html

• The Complete Collection of Data Science Cheat Sheets – Part 2

  A collection of cheat sheets that will help you prepare for a technical interview on Data Structures & Algorithms, Machine learning, Deep Learning, Natural Language Processing, Data Engineering, Web Frameworks.

  https://www.kdnuggets.com/2022/02/complete-collection-data-science-cheat-sheets-part-2.html

• Data Mesh & Its Distributed Data Architecture

  Going forward, data professionals have found a new way to address the scalability of sources through data mesh.

  https://www.kdnuggets.com/2022/02/data-mesh-distributed-data-architecture.html

• The Complete Collection of Data Science Cheat Sheets – Part 1

  A collection of cheat sheets that will help you prepare for a technical interview, assessment tests, class presentation, and help you revise core data science concepts.

  https://www.kdnuggets.com/2022/02/complete-collection-data-science-cheat-sheets-part-1.html

• 8 Best Data Science Courses to Enroll in 2022 For Steep Career Advancement

  Here is the list of the top 8 data science courses and programs that you can consider for upskilling yourself and get the best data scientist job in 2022.

  https://www.kdnuggets.com/2022/02/scaler-8-best-data-science-courses-enroll-2022-steep-career-advancement.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

• SQL Interview Questions for Experienced Professionals

  This article will show you what SQL concepts you should know as an experienced professional.

  https://www.kdnuggets.com/2022/01/sql-interview-questions-experienced-professionals.html

• How AI/ML Technology Integration Will Help Business in Achieving Goals in 2022

  AI/ML systems have a wide range of applications in a variety of industries and sectors, and this article highlights the top ways AI/ML will impact your small business in 2022.

  https://www.kdnuggets.com/2021/12/aiml-technology-integration-help-business-achieving-goals-2022.html

• Alternative Feature Selection Methods in Machine Learning

  Feature selection methodologies go beyond filter, wrapper and embedded methods. In this article, I describe 3 alternative algorithms to select predictive features based on a feature importance score.

  https://www.kdnuggets.com/2021/12/alternative-feature-selection-methods-machine-learning.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

• 6 Predictive Models Every Beginner Data Scientist Should Master">6 Predictive Models Every Beginner Data Scientist Should Master

  Data Science models come with different flavors and techniques — luckily, most advanced models are based on a couple of fundamentals. Which models should you learn when you want to begin a career as Data Scientist? This post brings you 6 models that are widely used in the industry, either in standalone form or as a building block for other advanced techniques.

  https://www.kdnuggets.com/2021/12/6-predictive-models-every-beginner-data-scientist-master.html

• Feature Selection: Where Science Meets Art

  From heuristic to algorithmic feature selection techniques for data science projects.

  https://www.kdnuggets.com/2021/12/feature-selection-science-meets-art.html

• Main 2021 Developments and Key 2022 Trends in AI, Data Science, Machine Learning Technology

  Our panel of leading experts reviews 2021 main developments and examines the key trends in AI, Data Science, Machine Learning, and Deep Learning Technology.

  https://www.kdnuggets.com/2021/12/trends-ai-data-science-ml-technology.html

• Should You Become a Freelance Artificial Intelligence Engineer?

  Take the first step towards your machine learning engineering career and explore the UC San Diego Extension Machine Learning Engineering Bootcamp today. Those with prior software engineering or data science experience are encouraged to apply.

  https://www.kdnuggets.com/2021/12/ucsd-become-freelance-artificial-intelligence-engineer.html

• Movie Recommendations with Spark Collaborative Filtering

  Not sure what movie to watch? Ask your recommender system.

  https://www.kdnuggets.com/2021/12/movie-recommendations-spark-collaborative-filtering.html

• KDnuggets™ News 21:n45, Dec 1: Most Common SQL Mistakes on Data Science Interviews; Why Machine Learning Engineers are Replacing Data Scientists

  Most Common SQL Mistakes on Data Science Interviews; Why Machine Learning Engineers are Replacing Data Scientists; Vote in new KDnuggets Poll: What Percentage of Your Machine Learning Models Have Been Deployed? KDnuggets: Personal History and Nuggets of Experience.

  https://www.kdnuggets.com/2021/n45.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

• Can You Become a Data Scientist Online?

  Until November 29th, you can join over 1.5 million students around the globe and gain the skills of successful data science professionals with unlimited annual access to the 365 Data Science Program at 72% OFF. Read on to learn more!

  https://www.kdnuggets.com/2021/11/365datascience-become-data-scientist-online.html

• On-Device Deep Learning: PyTorch Mobile and TensorFlow Lite

  PyTorch and TensorFlow are the two leading AI/ML Frameworks. In this article, we take a look at their on-device counterparts PyTorch Mobile and TensorFlow Lite and examine them more deeply from the perspective of someone who wishes to develop and deploy models for use on mobile platforms.

  https://www.kdnuggets.com/2021/11/on-device-deep-learning-pytorch-mobile-tensorflow-lite.html

• AI meets BI: Key capabilities to look for in a modern BI platform

  With the customer at its heart, modern augmented BI platforms no longer require scripting/coding skills or the knowledge to build the back-end data models, empowering even laymen to harness the power of raw data. As a user, here are the top AI capabilities that you need to look for in BI software.

  https://www.kdnuggets.com/2021/11/zoho-ai-meets-bi-key-capabilities-platform.html

• 10 AI Project Ideas in Computer Vision

  The field of computer vision has seen the development of very powerful applications leveraging machine learning. These projects will introduce you to these techniques and guide you to more advanced practice to gain a deeper appreciation for the sophistication now available.

  https://www.kdnuggets.com/2021/11/10-ai-project-ideas-computer-vision.html

• The Common Misconceptions About Machine Learning

  Beginners in the field can often have many misconceptions about machine learning that sometimes can be a make-it-or-break-it moment for the individual switching careers or starting fresh. This article clearly describes the ground truth realities about learning new ML skills and eventually working professionally as a machine learning engineer.

  https://www.kdnuggets.com/2021/11/common-misconception-about-machine-learning.html

• The Best Ways for Data Professionals to Market AWS Skills in 2022

  Knowing your way around Amazon Web Services (AWS) is increasingly useful. Here are five ways to market your AWS skills in today’s job market.

  https://www.kdnuggets.com/2021/11/best-ways-data-professionals-market-aws-skills.html

• Visual Scoring Techniques for Classification Models

  Read this article assessing a model performance in a broader context.

  https://www.kdnuggets.com/2021/11/visual-scoring-techniques-classification-models.html

• Multivariate Time Series Analysis with an LSTM based RNN

  Check out this codeless solution using the Keras integration.

  https://www.kdnuggets.com/2021/10/multivariate-time-series-analysis-lstm-based-rnn.html

• ETL and ELT: A Guide and Market Analysis

  ETL and related techniques remain a powerful and foundational tool in the data industry. We explain what ETL is and how ETL and ELT processes have evolved over the years, with a close eye toward how third-generation ETL tools are about to disrupt standard data processing practices.

  https://www.kdnuggets.com/2021/10/etl-elt-guide-market-analysis.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

• 365 Data Science courses free until 18 November">365 Data Science courses free until 18 November

  365 Data Science, an online educational platform providing beginner-to-advanced courses for data science and business analytics professionals, will unlock the entire library of courses, hands-on exercises, certificate exams, and resume builder for a full 30-day period from Oct. 18 to Nov. 18.

  https://www.kdnuggets.com/2021/10/365datascience-courses-free.html

• Guide To Finding The Right Predictive Maintenance Machine Learning Techniques

  What happens to a life so dependent on machines, when that particular machine breaks down? This is precisely why there’s a dire need for predictive maintenance with machine learning.

  https://www.kdnuggets.com/2021/10/guide-right-predictive-maintenance-machine-learning-techniques.html

• How to do “Limitless” Math in Python

  How to perform arbitrary-precision computation and much more math (and fast too) than what is possible with the built-in math library in Python.

  https://www.kdnuggets.com/2021/10/limitless-math-python.html

• 38 Free Courses on Coursera for Data Science">38 Free Courses on Coursera for Data Science

  There are so many online resources for learning data science, and a great deal of it can be used at no cost. This collection of free courses hosted by Coursera will help you enhance your data science and machine learning skills, no matter your current level of expertise.

  https://www.kdnuggets.com/2021/10/38-free-courses-coursera-datascience.html

• Eight Data Science Specializations, and Why You Should Pick One

  With so many Data Science specializations, where should you focus? The Pace University online Master of Science in Data Science features elective courses which allow you to focus on topics that suit your career path so that you can begin to develop a unique specialization.

  https://www.kdnuggets.com/2021/10/pace-eight-data-science-specializations.html

• Data science SQL interview questions from top tech firms">Data science SQL interview questions from top tech firms

  As a data scientist, there is one thing you really need to understand and know how to handle: data. With SQL being a foundational technical approach for working with data, it should not be surprising that the top tech companies will ask about your SQL skills during an interview. Here, we cover the key concepts tested so you can best prepare for your next data science interview.

  https://www.kdnuggets.com/2021/10/data-science-sql-interview-questions.html

• Introduction to PyTorch Lightning">Introduction to PyTorch Lightning

  PyTorch Lightning is a high-level programming layer built on top of PyTorch. It makes building and training models faster, easier, and more reliable.

  https://www.kdnuggets.com/2021/10/introduction-pytorch-lightning.html

• Computer Vision in Agriculture

  Deep learning isn’t just for placing ads or identifying cats anymore. Instead, a slew of young startups have started to incorporate the advances in computer vision made possible through larger and larger neural networks to real working robots in the fields.

  https://www.kdnuggets.com/2021/09/computer-vision-agriculture.html

• 9 Outstanding Reasons to Learn Python for Finance

  Is Python good for learning finance and working in the financial world? The answer is not only a resounding YES, but yes for nine very good reasons. This article gets into the details behind why Python is a must-know programming language for anyone who wants to work in the financial sector.

  https://www.kdnuggets.com/2021/09/9-outstanding-reasons-learn-python-finance.html

• How to be a Data Scientist without a STEM degree">How to be a Data Scientist without a STEM degree

  Breaking into data science as a professional does require technical skills, a well-honed knack for problem-solving, and a willingness to swim in oceans of data. Maybe you are coming in as a career change or ready to take a new learning path in life--without having previously earned an advanced degree in a STEM field. Follow these tips to find your way into this high-demand and interesting field.

  https://www.kdnuggets.com/2021/09/data-scientist-without-stem-degree.html

• What Is The Real Difference Between Data Engineers and Data Scientists?

  To launch your data career, you’ll need both theoretical knowledge and applied skills. Bootcamp programs like Springboard’s Data Science Career Track and Data Engineering Career Track can help make you job-ready through hands-on, project-based learning and one-on-one mentorship. Wondering which data career path is right for you? Read on to find out.

  https://www.kdnuggets.com/2021/09/springboard-difference-data-engineers-data-scientists.html

• Working with Python APIs For Data Science Project

  In this article, we will work with YouTube Python API to collect video statistics from our channel using the requests python library to make an API call and save it as a Pandas DataFrame.

  https://www.kdnuggets.com/2021/09/python-apis-data-science-project.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

• How is Machine Learning Beneficial in Mobile App Development?

  Mobile app developers have a lot to gain by implementing AI & Machine Learning from the revolutionary changes that these disruptive technologies can offer. This is due to AI and ML's potential to strengthen mobile applications, providing for smoother user experiences capable of leveraging powerful features.

  https://www.kdnuggets.com/2021/09/machine-learning-beneficial-mobile-app-development.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

• 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 Visualization is Transforming Exploratory Data Analysis">How 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

• 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

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

• Advice for Learning Data Science from Google’s Director of Research">Advice 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

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

• How to Get Practical Data Science Experience to be Career-Ready">How to Get Practical Data Science Experience to be Career-Ready

  Becoming a professional in the field of data science takes more than just book-smarts. You need to have experience with real-world data sets, frequently-used tools, and an intuition for solutions that you can only gain from hands-on experience. These resources will jump start developing your practical skills.

  https://www.kdnuggets.com/2021/07/practical-data-science-experience-career-ready.html

• Top Stories, Jun 28 – Jul 4: 5 Lessons McKinsey Taught Me That Will Make You a Better Data Scientist

  Also: What will the demand for Data Scientists be in 10 years? Will Data Scientists be extinct?; Add A New Dimension To Your Photos Using Python; Managing Your Reusable Python Code as a Data Scientist; Data Scientists are from Mars and Software Developers are from Venus

  https://www.kdnuggets.com/2021/07/top-news-week-0628-0704.html

• SAS® Visual Data Science Decisioning powered by SAS® Viya®: Free Trial

  SAS® Visual Data Science Decisioning provides the ultimate analytics experience. Start your free trial and get access to the latest in data visualization, machine learning, forecasting, model deployment and more.

  https://www.kdnuggets.com/2021/06/sas-viya-visual-data-science-free-trial.html

• BigQuery vs Snowflake: A Comparison of Data Warehouse Giants

  In this article we are going to compare the two topmost data warehouses: BigQuery and Snowflake.

  https://www.kdnuggets.com/2021/06/bigquery-snowflake-comparison-data-warehouse-giants.html

• DataOps: 5 things that you need to know

  DataOps (Data Operations) has assumed a critical role in the age of big data to drive definitive impact on business outcomes. This process-oriented and agile methodology synergizes the components of DevOps and the capabilities of data engineers and data scientists to support data-focused workloads in enterprises. Here is a detailed look at DataOps.

  https://www.kdnuggets.com/2021/05/dataops-5-things-need-know.html

• Data careers are NOT one-size fits all! Tips for uncovering your ideal role in the data space

  Thriving as a data professional is about more than just making good money! It’s about FULFILLMENT & IMPACT. In this article, I will help you discover the BEST data role for you given your unique skill sets, personality & goals.

  https://www.kdnuggets.com/2021/04/data-careers-not-one-size-fits-all.html

• How to ace A/B Testing Data Science Interviews">How to ace A/B Testing Data Science Interviews

  Understanding the process of A/B testing and knowing how to discuss this approach during data science job interviews can give you a leg up over other candidates. This mock interview provides a step-by-step guide through how to demonstrate your mastery of the key concepts and logical considerations.

  https://www.kdnuggets.com/2021/04/ab-testing-data-science-interviews.html

• 10 Must-Know Statistical Concepts for Data Scientists

  Statistics is a building block of data science. If you are working or plan to work in this field, then you will encounter the fundamental concepts reviewed for you here. Certainly, there is much more to learn in statistics, but once you understand these basics, then you can steadily build your way up to advanced topics.

  https://www.kdnuggets.com/2021/04/10-statistical-concepts-data-scientists.html

• Data Science 101: Normalization, Standardization, and Regularization

  Normalization, standardization, and regularization all sound similar. However, each plays a unique role in your data preparation and model building process, so you must know when and how to use these important procedures.

  https://www.kdnuggets.com/2021/04/data-science-101-normalization-standardization-regularization.html

• Introducing dbt, the ETL and ELT Disrupter

  Moving and processing data is happening 24/7/365 world-wide at massive scales that only get larger by the hour. Tools exist to introduce efficiencies in how data can be extracted from sources, transformed through calculations, and loaded into target data repositories. However, on their own, these tools can introduce some restrictions in the processing, especially for the needs of data analytics and data science.

  https://www.kdnuggets.com/2021/03/dbt-etl-elt-disrupter.html

• Metric Matters, Part 1: Evaluating Classification Models

  You have many options when choosing metrics for evaluating your machine learning models. Select the right one for your situation with this guide that considers metrics for classification models.

  https://www.kdnuggets.com/2021/03/metrics-evaluating-classification-models-part1.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

• Are You Still Using Pandas to Process Big Data in 2021? Here are two better options">Are You Still Using Pandas to Process Big Data in 2021? Here are two better options

  When its time to handle a lot of data -- so much that you are in the realm of Big Data -- what tools can you use to wrangle the data, especially in a notebook environment? Pandas doesn’t handle really Big Data very well, but two other libraries do. So, which one is better and faster?

  https://www.kdnuggets.com/2021/03/pandas-big-data-better-options.html

• 6 Data Science Certificates To Level Up Your Career

  Anyone looking to obtain a data science certificate to prove their ability in the field will find a range of options exist. We review several valuable certificates to consider that will definitely pump up your resume and portfolio to get you closer to your dream job.

  https://www.kdnuggets.com/2021/02/6-data-science-certificates.html

• 10 resources for data science self-study

  Many resources exist for the self-study of data science. In our modern age of information technology, an enormous amount of free learning resources are available to anyone, and with effort and dedication, you can master the fundamentals of data science.

  https://www.kdnuggets.com/2021/02/10-resources-data-science-self-study.html

• A Critical Comparison of Machine Learning Platforms in an Evolving Market

  There’s a clear inclination towards the MLaaS model across industries, given the fact that companies today have an option to select from a wide range of solutions that can cater to diverse business needs. Here is a look at 3 of the top ML platforms for data excellence.

  https://www.kdnuggets.com/2021/02/critical-comparison-machine-learning-platforms-evolving-market.html

• 7 Most Recommended Skills to Learn to be a Data Scientist

  The Data Scientist professional has emerged as a true interdisciplinary role that spans a variety of skills, theoretical and practical. For the core, day-to-day activities, many critical requirements that enable the delivery of real business value reach well outside the realm of machine learning, and should be mastered by those aspiring to the field.

  https://www.kdnuggets.com/2021/02/7-most-recommended-skills-data-scientist.html

• How to create stunning visualizations using python from scratch">How to create stunning visualizations using python from scratch

  Data science and data analytics can be beautiful things. Not only because of the insights and enhancements to decision-making they can provide, but because of the rich visualizations about the data that can be created. Following this step-by-step guide using the Matplotlib and Seaborn libraries will help you improve the presentation and effective communication of your work.

  https://www.kdnuggets.com/2021/02/stunning-visualizations-using-python.html

• Is M.Tech in Data Science Worth It?

  Is M.Tech in Data Science worth it or should you learn using just online courses and projects. Let's try to find the answer to that question.

  https://www.kdnuggets.com/2021/01/greatlearning-mtech-data-science.html

• Cloud Data Warehouse is The Future of Data Storage

  Today, cloud data storage accounts for 45% of all enterprise data and by Q2 2021, that number could grow to 53%. Now is the time to embrace cloud than now.

  https://www.kdnuggets.com/2021/01/cloud-data-warehouse-future-data-storage.html

• 11 Industrial AI Trends that will Dominate the World in 2021

  These trends broadly cover the three themes of: Where will businesses adopt AI in 2021? How will AI become more accessible? How will AI capabilities evolve?

  https://www.kdnuggets.com/2021/01/11-industrial-ai-trends-dominate-2021.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

• 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

• 20 Core Data Science Concepts for Beginners">20 Core Data Science Concepts for Beginners

  With so much to learn and so many advancements to follow in the field of data science, there are a core set of foundational concepts that remain essential. Twenty of these ideas are highlighted here that are key to review when preparing for a job interview or just to refresh your appreciation of the basics.

  https://www.kdnuggets.com/2020/12/20-core-data-science-concepts-beginners.html

• Why the Future of ETL Is Not ELT, But EL(T)">Why the Future of ETL Is Not ELT, But EL(T)

  The well-established technologies and tools around ETL (Extract, Transform, Load) are undergoing a potential paradigm shift with new approaches to data storage and expanding cloud-based compute. Decoupling the EL from T could reconcile analytics and operational data management use cases, in a new landscape where data warehouses and data lakes are merging.

  https://www.kdnuggets.com/2020/12/future-etl-is-elt.html

• 14 Data Science projects to improve your skills

  There's a lot of data out there and so many data science techniques to master or review. Check out these great project ideas from easy to advanced difficulty levels to develop new skills and strengthen your portfolio.

  https://www.kdnuggets.com/2020/12/14-data-science-projects-improve-skills.html

• TabPy: Combining Python and Tableau">TabPy: Combining Python and Tableau

  This article demonstrates how to get started using Python in Tableau.

  https://www.kdnuggets.com/2020/11/tabpy-combining-python-tableau.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

• 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

• The Best Data Science Certification You’ve Never Heard Of">The Best Data Science Certification You’ve Never Heard Of

  The CDMP is the best data strategy certification you’ve never heard of. (And honestly, when you consider the fact that you’re probably working a job that didn’t exist ten years ago, it’s not surprising that this certification isn’t widespread just yet.)

  https://www.kdnuggets.com/2020/11/best-data-science-certification-never-heard.html

• Data scientist or machine learning engineer? Which is a better career option?

  In order to build automated data processing systems, we require professionals like Machine Learning Engineers and Data Scientists. But which of these is a better career option right now? Read on to find out.

  https://www.kdnuggets.com/2020/11/greatlearning-data-scientist-machine-learning-engineer.html

• Stop Running Jupyter Notebooks From Your Command Line

  Instead, run your Jupyter Notebook as a stand alone web app.

  https://www.kdnuggets.com/2020/10/stop-running-jupyter-notebooks-command-line.html

• Comparing the Top Business Intelligence Tools: Power BI vs Tableau vs Qlik vs Domo

  How smart are your organizations’ decisions? Do you have the right information to make those decisions in the first place?

  https://www.kdnuggets.com/2020/10/comparing-top-business-intelligence-tools.html

• Online Certificates/Courses in AI, Data Science, Machine Learning from Top Universities">Online Certificates/Courses in AI, Data Science, Machine Learning from Top Universities

  We present the online courses and certificates in AI, Data Science, Machine Learning, and related topics from the top 20 universities in the world.

  https://www.kdnuggets.com/2020/09/online-certificates-ai-data-science-machine-learning-top.html

• The Maslow’s hierarchy your data science team needs

  Domino Data Lab was announced as a leader for the second year in a row in the recently released “Forrester Wave™: Notebook-based Predictive Analytics and Machine Learning (PAML), Q3 2020” analyst report. True to our data science roots, we’ve built a Maslow’s hierarchy of data science team needs.

  https://www.kdnuggets.com/2020/09/domino-leader-forrester-paml-data-science-team.html

• 8 AI/Machine Learning Projects To Make Your Portfolio Stand Out">8 AI/Machine Learning Projects To Make Your Portfolio Stand Out

  If you are just starting down a path toward a career in Data Science, or you are already a seasoned practitioner, then keeping active to advance your experience through side projects is invaluable to take you to the next professional level. These eight interesting project ideas with source code and reference articles will jump start you to thinking outside of the box.

  https://www.kdnuggets.com/2020/09/8-ml-ai-projects-stand-out.html

• Content-Based Recommendation System using Word Embeddings

  This article explores how average Word2Vec and TF-IDF Word2Vec can be used to build a recommendation engine.

  https://www.kdnuggets.com/2020/08/content-based-recommendation-system-word-embeddings.html

• Unit Test Your Data Pipeline, You Will Thank Yourself Later">Unit Test Your Data Pipeline, You Will Thank Yourself Later

  While you cannot test model output, at least you should test that inputs are correct. Compared to the time you invest in writing unit tests, good pieces of simple tests will save you much more time later, especially when working on large projects or big data.

  https://www.kdnuggets.com/2020/08/unit-test-data-pipeline-thank-yourself-later.html

• Fuzzy Joins in Python with d6tjoin

  Combining different data sources is a time suck! d6tjoin is a python library that lets you join pandas dataframes quickly and efficiently.

  https://www.kdnuggets.com/2020/07/fuzzy-joins-python-d6tjoin.html

• Awesome Machine Learning and AI Courses">Awesome Machine Learning and AI Courses

  Check out this list of awesome, free machine learning and artificial intelligence courses with video lectures.

  https://www.kdnuggets.com/2020/07/awesome-machine-learning-ai-courses.html

• Building a Content-Based Book Recommendation Engine

  In this blog, we will see how we can build a simple content-based recommender system using Goodreads data.

  https://www.kdnuggets.com/2020/07/building-content-based-book-recommendation-engine.html

• A Complete Guide To Survival Analysis In Python, part 2

  Continuing with the second of this three-part series covering a step-by-step review of statistical survival analysis, we look at a detailed example implementing the Kaplan-Meier fitter theory as well as the Nelson-Aalen fitter theory, both with examples and shared code.

  https://www.kdnuggets.com/2020/07/guide-survival-analysis-python-part-2.html

• 7 Signs you are data literate

  Understanding data is key to being a Data Scientist. But, how can you know if you might be a good fit for the field when you haven't worked with much data? These telltale signs will suggest you are competent to work with data, and that you might have a talent for being data literate.

  https://www.kdnuggets.com/2020/07/7-signs-data-literate.html

• A Complete Guide To Survival Analysis In Python, part 1">A Complete Guide To Survival Analysis In Python, part 1

  This three-part series covers a review with step-by-step explanations and code for how to perform statistical survival analysis used to investigate the time some event takes to occur, such as patient survival during the COVID-19 pandemic, the time to failure of engineering products, or even the time to closing a sale after an initial customer contact.

  https://www.kdnuggets.com/2020/07/complete-guide-survival-analysis-python-part1.html

• Machine Learning Engineer vs Data Scientist (Is Data Science Over?)

  What has been happening to the definition of Data Scientist over the past 5 years? Does it still exist or has it morphed into a new version of its old self? Learn more about the recent trends in job descriptions and salaries for data scientists, ML engineers, and others to best understand the best fit for your career trajectory and interests.

  https://www.kdnuggets.com/2020/06/machine-learning-engineer-vs-data-scientist.html

• LightGBM: A Highly-Efficient Gradient Boosting Decision Tree

  LightGBM is a histogram-based algorithm which places continuous values into discrete bins, which leads to faster training and more efficient memory usage. In this piece, we’ll explore LightGBM in depth.

  https://www.kdnuggets.com/2020/06/lightgbm-gradient-boosting-decision-tree.html

• Top 6 Reasons Data Scientists Should Know Java

  There are many reasons why data scientists should learn Java. Read this overview of 6 specific reasons to help decide if Java might be right for your projects.

  https://www.kdnuggets.com/2020/06/top-6-reasons-data-scientists-know-java.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

• What You Need to Know About Deep Reinforcement Learning

  How does deep learning solve the challenges of scale and complexity in reinforcement learning? Learn how combining these approaches will make more progress toward the notion of Artificial General Intelligence.

  https://www.kdnuggets.com/2020/05/deep-reinforcement-learning.html

• Chatbots in a Nutshell

  Marketing scientist Kevin Gray asks Dr. Anna Farzindar of the University of Southern California about chatbots and the ways they are used.

  https://www.kdnuggets.com/2020/05/chatbots-nutshell.html

• Top 10 Data Visualization Tools for Every Data Scientist">Top 10 Data Visualization Tools for Every Data Scientist

  At present, the data scientist is one of the most sought after professions. That’s one of the main reasons why we decided to cover the latest data visualization tools that every data scientist can use to make their work more effective.

  https://www.kdnuggets.com/2020/05/top-10-data-visualization-tools-every-data-scientist.html

• Find Your Perfect Fit: A Quick Guide for Job Roles in the Data World

  Data related positions are considered the hottest in the job market during the last couple of years. While everyone wants to join the party and enter this fascinating field, it is essential to first get an understanding. In this quick guide, I’ll do my best to dispel the confusion by crystalizing the essence of the different positions.

  https://www.kdnuggets.com/2020/04/find-perfect-fit-data-job-roles-guide.html

• State of the Machine Learning and AI Industry

  Enterprises are struggling to launch machine learning models that encapsulate the optimization of business processes. These are now the essential components of data-driven applications and AI services that can improve legacy rule-based business processes, increase productivity, and deliver results. In the current state of the industry, many companies are turning to off-the-shelf platforms to increase expectations for success in applying machine learning.

  https://www.kdnuggets.com/2020/04/machine-learning-ai-industry.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

• Python for data analysis… is it really that simple?!?">Python for data analysis… is it really that simple?!?

  The article addresses a simple data analytics problem, comparing a Python and Pandas solution to an R solution (using plyr, dplyr, and data.table), as well as kdb+ and BigQuery solutions. Performance improvement tricks for these solutions are then covered, as are parallel/cluster computing approaches and their limitations.

  https://www.kdnuggets.com/2020/04/python-data-analysis-really-that-simple.html

• Building a Mature Machine Learning Team

  After spending a lot of time thinking about the paths that software companies take toward ML maturity, this framework was created to follow as you adopt ML and then mature as an organization. The framework covers every aspect of building a team including product, process, technical, and organizational readiness, as well as recognizes the importance of cross-functional expertise and process improvements for bringing AI-driven products to market.

  https://www.kdnuggets.com/2020/03/mature-machine-learning-team.html

• The Death of Data Scientists – will AutoML replace them?">The Death of Data Scientists – will AutoML replace them?

  Soon after tech giants Google and Microsoft introduced their AutoML services to the world, the popularity and interest in these services skyrocketed. We first review AutoML, compare the platforms available, and then test them out against real data scientists to answer the question: will AutoML replace us?

  https://www.kdnuggets.com/2020/02/data-scientists-automl-replace.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

• Why Did I Reject a Data Scientist Job?">Why Did I Reject a Data Scientist Job?

  Snagging that job as a Data Scientist might not be exactly what you were expecting. Consider this advice on carefully considering job titles with what the position might really be like day-to-day.

  https://www.kdnuggets.com/2020/02/why-reject-data-scientist-job.html

• How to land a Data Scientist job at your dream company">How to land a Data Scientist job at your dream company

  Job hunting for anyone just starting out as a data scientist can require grit, passion, and perseverance before finding the best opportunity. Follow this career search journey to learn what it took -- and the learning resources used -- to land the dream job.

  https://www.kdnuggets.com/2020/01/data-scientist-job-dream-company.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

• The Data Science Interview Study Guide

  Preparing for a job interview can be a full-time job, and Data Science interviews are no different. Here are 121 resources that can help you study and quiz your way to landing your dream data science job.

  https://www.kdnuggets.com/2020/01/data-science-interview-study-guide.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

• A Comprehensive Guide to Natural Language Generation

  Follow this overview of Natural Language Generation covering its applications in theory and practice. The evolution of NLG architecture is also described from simple gap-filling to dynamic document creation along with a summary of the most popular NLG models.

  https://www.kdnuggets.com/2020/01/guide-natural-language-generation.html

• Why Python is One of the Most Preferred Languages for Data Science?

  Why do most data scientists love Python? Learn more about how so many well-developed Python packages can help you accomplish your crucial data science tasks.

  https://www.kdnuggets.com/2020/01/python-preferred-languages-data-science.html

• Predict Electricity Consumption Using Time Series Analysis">Predict Electricity Consumption Using Time Series Analysis

  Time series forecasting is a technique for the prediction of events through a sequence of time. In this post, we will be taking a small forecasting problem and try to solve it till the end learning time series forecasting alongside.

  https://www.kdnuggets.com/2020/01/predict-electricity-consumption-time-series-analysis.html

• Automatic Text Summarization in a Nutshell

  Marketing scientist Kevin Gray asks Dr. Anna Farzindar of the University of Southern California about Automatic Text Summarization and the various ways it is used.

  https://www.kdnuggets.com/2019/12/automatic-text-summarization-nutshell.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

• Data Science Curriculum Roadmap">Data Science Curriculum Roadmap

  What follows is a set of broad recommendations, and it will inevitably require a lot of adjustments in each implementation. Given that caveat, here are our curriculum recommendations.

  https://www.kdnuggets.com/2019/12/data-science-curriculum-roadmap.html

• Top 7 Data Science Use Cases in Trust and Security

  What are trust and safety? What is the role of trust and security in the modern world? Read this overview of 7 data science application use cases in the realm of trust and security.

  https://www.kdnuggets.com/2019/12/top-7-data-science-use-cases-trust-security.html

• The Future of Careers in Data Science & Analysis">The Future of Careers in Data Science & Analysis

  As the fields of data science and analysis continue to expand, the next crop of bright minds is always needed. Learn more about the nuances of these jobs and find where you can fit in for a rewarding and interesting career.

  https://www.kdnuggets.com/2019/11/future-careers-data-science-analysis.html

• Top 8 Data Science Use Cases in Marketing

  In this article, we want to highlight some key data science use cases in marketing. Let us concentrate on several instances that present particular interest and managed to prove their efficiency in the course of time.

  https://www.kdnuggets.com/2019/11/top-8-data-science-use-cases-marketing.html

• 10 Free Must-read Books on AI">10 Free Must-read Books on AI

  Artificial Intelligence continues to fill the media headlines while scientists and engineers rapidly expand its capabilities and applications. With such explosive growth in the field, there is a great deal to learn. Dive into these 10 free books that are must-reads to support your AI study and work.

  https://www.kdnuggets.com/2019/11/10-free-must-read-books-ai.html

• How to Become a Successful Healthcare Data Analyst

  Are you interested in starting your career in the data analysis domain? Read this informative blog on how to get your career off the ground.

  https://www.kdnuggets.com/2019/11/become-successful-healthcare-data-analyst.html

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

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

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

• How to Become a (Good) Data Scientist – Beginner Guide">How to Become a (Good) Data Scientist – Beginner Guide

  A guide covering the things you should learn to become a data scientist, including the basics of business intelligence, statistics, programming, and machine learning.

  https://www.kdnuggets.com/2019/10/good-data-scientist-beginner-guide.html

• The 4 Quadrants of Data Science Skills and 7 Principles for Creating a Viral Data Visualization">The 4 Quadrants of Data Science Skills and 7 Principles for Creating a Viral Data Visualization

  As a data scientist, your most important skill is creating meaningful visualizations to disseminate knowledge and impact your organization or client. These seven principals will guide you toward developing charts with clarity, as exemplified with data from a recent KDnuggets poll.

  https://www.kdnuggets.com/2019/10/4-quadrants-data-science-skills-data-visualization.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