Search results for AI ML Programming Research

Found 620 documents, 5942 searched:

• How to Get a Job as a Data Scientist">How to Get a Job as a Data Scientist

  Here’s a step-by-step guide to starting your career in data science.

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

• Can Data Science Be Agile? Implementing Best Agile Practices to Your Data Science Process

  Agile is not reserved for software developers only -- that's a myth. While these effective strategies are not commonly used by data scientists today and some aspects of data science make Agile a bit tricky, the methodology offers plenty of benefits to data science projects that can increase the effectiveness of your process and bring more success to your outcomes.

  https://www.kdnuggets.com/2021/01/data-science-agile-best-practices.html

• My Data Science Learning Journey So Far">My Data Science Learning Journey So Far

  These are some obstacles the author faced in their data science learning journey in the past year, including how much time it took to overcome each obstacle and what it has taught the author.

  https://www.kdnuggets.com/2021/01/data-science-learning-journey.html

• The Four Jobs of the Data Scientist">The Four Jobs of the Data Scientist

  So, what do you do for a living? Sometimes, the answer to that question can feel like, "everything!" Well, for the Data Scientist, an extreme sense of being a "jack of all trades" is common. In fact, four such trades can be defined that a top-quality Data Scientist will iterate through during any one project.

  https://www.kdnuggets.com/2021/01/four-jobs-data-scientist.html

• The Best Tool for Data Blending is KNIME

  These are the lessons and best practices I learned in many years of experience in data blending, and the software that became my most important tool in my day-to-day work.

  https://www.kdnuggets.com/2021/01/best-tool-data-blending-knime.html

• 5 Tools for Effortless Data Science

  The sixth tool is coffee.

  https://www.kdnuggets.com/2021/01/5-tools-effortless-data-science.html

• Where is Marketing Data Science Headed?

  Marketing data science - data science related to marketing - is now a significant part of marketing. Some of it directly competes with traditional marketing research and many marketing researchers may wonder what the future holds in store for it.

  https://www.kdnuggets.com/2021/01/marketing-data-science-headed.html

• 15 Free Data Science, Machine Learning & Statistics eBooks for 2021">15 Free Data Science, Machine Learning & Statistics eBooks for 2021

  We present a curated list of 15 free eBooks compiled in a single location to close out the year.

  https://www.kdnuggets.com/2020/12/15-free-data-science-machine-learning-statistics-ebooks-2021.html

• Monte Carlo integration in Python">Monte Carlo integration in Python

  A famous Casino-inspired trick for data science, statistics, and all of science. How to do it in Python?

  https://www.kdnuggets.com/2020/12/monte-carlo-integration-python.html

• 10 Python Skills They Don’t Teach in Bootcamp

  Ascend to new heights in Data Science and Machine Learning with this thrilling list of coding tips.

  https://www.kdnuggets.com/2020/12/10-python-skills-dont-teach-bootcamp.html

• Introduction to Data Engineering">Introduction to Data Engineering

  The Q&A for the most frequently asked questions about Data Engineering: What does a data engineer do? What is a data pipeline? What is a data warehouse? How is a data engineer different from a data scientist? What skills and programming languages do you need to learn to become a data engineer?

  https://www.kdnuggets.com/2020/12/introduction-data-engineering.html

• 10 Python Skills for Beginners

  Python is the fastest growing, most-beloved programming language. Get started with these Data Science tips.

  https://www.kdnuggets.com/2020/12/10-python-skills-beginners.html

• Simple & Intuitive Ensemble Learning in R

  Read about metaEnsembleR, an R package for heterogeneous ensemble meta-learning (classification and regression) that is fully-automated.

  https://www.kdnuggets.com/2020/12/simple-intuitive-meta-learning-r.html

• Learn Deep Learning with this Free Course from Yann LeCun">Learn Deep Learning with this Free Course from Yann LeCun

  Here is a freely-available NYU course on deep learning to check out from Yann LeCun and Alfredo Canziani, including videos, slides, and other helpful resources.

  https://www.kdnuggets.com/2020/11/learn-deep-learning-free-course-yann-lecun.html

• 5 Most Useful Machine Learning Tools every lazy full-stack data scientist should use

  If you consider yourself a Data Scientist who can take any project from data curation to solution deployment, then you know there are many tools available today to help you get the job done. The trouble is that there are too many choices. Here is a review of five sets of tools that should turn you into the most efficient full-stack data scientist possible.

  https://www.kdnuggets.com/2020/11/5-useful-machine-learning-tools.html

• Algorithms for Advanced Hyper-Parameter Optimization/Tuning

  In informed search, each iteration learns from the last, whereas in Grid and Random, modelling is all done at once and then the best is picked. In case for small datasets, GridSearch or RandomSearch would be fast and sufficient. AutoML approaches provide a neat solution to properly select the required hyperparameters that improve the model’s performance.

  https://www.kdnuggets.com/2020/11/algorithms-for-advanced-hyper-parameter-optimization-tuning.html

• Top Python Libraries for Deep Learning, Natural Language Processing & Computer Vision">Top Python Libraries for Deep Learning, Natural Language Processing & Computer Vision

  This article compiles the 30 top Python libraries for deep learning, natural language processing & computer vision, as best determined by KDnuggets staff.

  https://www.kdnuggets.com/2020/11/top-python-libraries-deep-learning-natural-language-processing-computer-vision.html

• My Data Science Online Learning Journey on Coursera

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

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

• 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

• Advice for Aspiring Data Scientists

  Are you a student of some type asking how to get into Data Science? You've come to the right place. Read on for both common and less basic advice on entering the field and excelling in the profession.

  https://www.kdnuggets.com/2020/10/advice-aspiring-data-scientists.html

• Software 2.0 takes shape

  Software developers remain in very high demand as many organizations continue to experience workloads that far exceed available talent. AI-enhanced approaches that automate more areas of the software development lifecycle are in development with interesting potentials for how machine learning and natural language processing can significantly impact how software is designed, developed, tested, and deployed in the future.

  https://www.kdnuggets.com/2020/10/software-20-takes-shape.html

• Behavior Analysis with Machine Learning and R: The free eBook

  Check out this new free ebook to learn how to leverage the power of machine learning to analyze behavioral patterns from sensor data and electronic records using R.

  https://www.kdnuggets.com/2020/10/behavior-analysis-machine-learning-r-free-ebook.html

• 10 Underrated Python Skills

  Tips for feature analysis, hyperparameter tuning, data visualization and more.

  https://www.kdnuggets.com/2020/10/10-underrated-python-skills.html

• Getting Started with PyTorch

  A practical walkthrough on how to use PyTorch for data analysis and inference.

  https://www.kdnuggets.com/2020/10/getting-started-pytorch.html

• 10 Best Machine Learning Courses in 2020">10 Best Machine Learning Courses in 2020

  If you are ready to take your career in machine learning to the next level, then these top 10 Machine Learning Courses covering both practical and theoretical work will help you excel.

  https://www.kdnuggets.com/2020/10/10-best-machine-learning-courses-2020.html

• Machine Learning from Scratch: Free Online Textbook">Machine Learning from Scratch: Free Online Textbook

  If you are looking for a machine learning starter that gets right to the core of the concepts and the implementation, then this new free textbook will help you dive in to ML engineering with ease. By focusing on the basics of the underlying algorithms, you will be quickly up and running with code you construct yourself.

  https://www.kdnuggets.com/2020/09/machine-learning-from-scratch-free-online-textbook.html

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

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

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

• Lessons From My First Kaggle Competition

  How I chose my first Kaggle competition to enter and what I learned from doing it.

  https://www.kdnuggets.com/2020/09/lessons-first-kaggle-competition.html

• Modern Data Science Skills: 8 Categories, Core Skills, and Hot Skills">Modern Data Science Skills: 8 Categories, Core Skills, and Hot Skills

  We analyze the results of the Data Science Skills poll, including 8 categories of skills, 13 core skills that over 50% of respondents have, the emerging/hot skills that data scientists want to learn, and what is the top skill that Data Scientists want to learn.

  https://www.kdnuggets.com/2020/09/modern-data-science-skills.html

• Top Online Masters in Analytics, Business Analytics, Data Science – Updated">Top Online Masters in Analytics, Business Analytics, Data Science – Updated

  We provide an updated list of best online Masters in AI, Analytics, and Data Science, including rankings, tuition, and duration of the education program.

  https://www.kdnuggets.com/2020/09/best-online-masters-data-science-analytics-online.html

• Microsoft’s DoWhy is a Cool Framework for Causal Inference

  Inspired by Judea Pearl’s do-calculus for causal inference, the open source framework provides a programmatic interface for popular causal inference methods.

  https://www.kdnuggets.com/2020/08/microsoft-dowhy-framework-causal-inference.html

• How to Optimize Your CV for a Data Scientist Career">How to Optimize Your CV for a Data Scientist Career

  As the number of data science positions continues to grow dramatically, so does the number of data scientists in the marketplace. Follow these expert tips and examples to help make your resume and job applications stand out in an increasingly competitive field.

  https://www.kdnuggets.com/2020/08/optimize-cv-data-scientist-career.html

• Must-read NLP and Deep Learning articles for Data Scientists">Must-read NLP and Deep Learning articles for Data Scientists

  NLP and deep learning continue to advance, nearly on a daily basis. Check out these recent must-read guides, feature articles, and other resources to keep you on top of the latest advancements and ahead of the curve.

  https://www.kdnuggets.com/2020/08/must-read-nlp-deep-learning-articles.html

• Rapid Python Model Deployment with FICO Xpress Insight

  The biggest hurdle in the use of data to create business value, is indeed the ability to operationalize analytics throughout the organization. Xpress Insight is geared to reduce the burden on IT and address their critical requirements while empowering business users to take ownership of decisions and change management.

  https://www.kdnuggets.com/2020/08/fico-xpress-insight-python-deployment.html

• Data Science Internship Interview Questions

  Data science is an attractive field because not only is it lucrative, but you can have opportunities to work on interesting projects, and you’re always learning new things. If you're trying to get started from the ground up, then review this guide to prepare for the interview essentials.

  https://www.kdnuggets.com/2020/08/data-science-internship-interview-questions.html

• Exploring GPT-3: A New Breakthrough in Language Generation

  GPT-3 is the largest natural language processing (NLP) transformer released to date, eclipsing the previous record, Microsoft Research’s Turing-NLG at 17B parameters, by about 10 times. This has resulted in an explosion of demos: some good, some bad, all interesting.

  https://www.kdnuggets.com/2020/08/exploring-gpt-3-breakthrough-language-generation.html

• Data Scientist Job Market 2020

  With an analysis of over a thousand Data Scientist job descriptions in the USA, check out the trends for 2020 and current expectations on new positions in the field, including credentials, experience, and programming languages.

  https://www.kdnuggets.com/2020/08/data-scientist-job-market-2020.html

• Netflix’s Polynote is a New Open Source Framework to Build Better Data Science Notebooks">Netflix’s Polynote is a New Open Source Framework to Build Better Data Science Notebooks

  The new notebook environment provides substantial improvements to streamline experimentation in machine learning workflows.

  https://www.kdnuggets.com/2020/08/netflix-polynote-open-source-framework-better-data-science-notebooks.html

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

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

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

• 5 Fantastic Natural Language Processing Books

  This curated collection of 5 natural language processing books attempts to cover a number of different aspects of the field, balancing the practical and the theoretical. Check out these 5 fantastic selections now in order to improve your NLP skills.

  https://www.kdnuggets.com/2020/07/5-fantastic-nlp-books.html

• Why would you put Scikit-learn in the browser?

  Honestly? I don’t know. But I do think WebAssembly is a good target for ML/AI deployment (in the browser and beyond).

  https://www.kdnuggets.com/2020/07/why-put-scikit-learn-browser.html

• Foundations of Data Science: The Free eBook

  As has become tradition on KDnuggets, let's start a new week with a new eBook. This time we check out a survey style text with a variety of topics, Foundations of Data Science.

  https://www.kdnuggets.com/2020/07/foundations-data-science-free-ebook.html

• PyTorch for Deep Learning: The Free eBook

  For this week's free eBook, check out the newly released Deep Learning with PyTorch from Manning, made freely available via PyTorch's website for a limited time. Grab it now!

  https://www.kdnuggets.com/2020/07/pytorch-deep-learning-free-ebook.html

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

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

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

• How to Prepare Your Data

  This is an overview of structuring, cleaning, and enriching raw data.

  https://www.kdnuggets.com/2020/06/how-prepare-your-data.html

• The Most Important Fundamentals of PyTorch you Should Know">The Most Important Fundamentals of PyTorch you Should Know

  PyTorch is a constantly developing deep learning framework with many exciting additions and features. We review its basic elements and show an example of building a simple Deep Neural Network (DNN) step-by-step.

  https://www.kdnuggets.com/2020/06/fundamentals-pytorch.html

• Best Machine Learning Youtube Videos Under 10 Minutes

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

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

• Faster machine learning on larger graphs with NumPy and Pandas

  One of the most exciting features of StellarGraph 1.0 is a new graph data structure — built using NumPy and Pandas — that results in significantly lower memory usage and faster construction times.

  https://www.kdnuggets.com/2020/05/faster-machine-learning-larger-graphs-numpy-pandas.html

• Interactive Machine Learning Experiments

  Dive into experimenting with machine learning techniques using this open-source collection of interactive demos built on multilayer perceptrons, convolutional neural networks, and recurrent neural networks. Each package consists of ready-to-try web browser interfaces and fully-developed notebooks for you to fine tune the training for better performance.

  https://www.kdnuggets.com/2020/05/interactive-machine-learning-experiments.html

• 10 Useful Machine Learning Practices For Python Developers

  While you may be a data scientist, you are still a developer at the core. This means your code should be skillful. Follow these 10 tips to make sure you quickly deliver bug-free machine learning solutions.

  https://www.kdnuggets.com/2020/05/10-useful-machine-learning-practices-python-developers.html

• Automated Machine Learning: The Free eBook">Automated Machine Learning: The Free eBook

  There is a lot to learn about automated machine learning theory and practice. This free eBook can get you started the right way.

  https://www.kdnuggets.com/2020/05/automated-machine-learning-free-ebook.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

• Beginners Learning Path for Machine Learning">Beginners Learning Path for Machine Learning

  So, you are interested in machine learning? Here is your complete learning path to start your career in the field.

  https://www.kdnuggets.com/2020/05/beginners-learning-path-machine-learning.html

• 10 Best Machine Learning Textbooks that All Data Scientists Should Read

  Check out these 10 books that can help data scientists and aspiring data scientists learn machine learning today.

  https://www.kdnuggets.com/2020/04/10-best-machine-learning-textbooks-data-scientists.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

• Free High-Quality Machine Learning & Data Science Books & Courses: Quarantine Edition">Free High-Quality Machine Learning & Data Science Books & Courses: Quarantine Edition

  If you find yourself quarantined and looking for free learning materials in the way of books and courses to sharpen your data science and machine learning skills, this collection of articles I have previously written curating such things is for you.

  https://www.kdnuggets.com/2020/04/machine-learning-data-science-books-courses-quarantine.html

• The Benefits & Examples of Using Apache Spark with PySpark

  Apache Spark runs fast, offers robust, distributed, fault-tolerant data objects, and integrates beautifully with the world of machine learning and graph analytics. Learn more here.

  https://www.kdnuggets.com/2020/04/benefits-apache-spark-pyspark.html

• Dive Into Deep Learning: The Free eBook

  This freely available text on deep learning is fully interactive and incredibly thorough. Check out "Dive Into Deep Learning" now and increase your neural networks theoretical understanding and practical implementation skills.

  https://www.kdnuggets.com/2020/04/dive-deep-learning-book.html

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

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

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

• Federated Learning: An Introduction

  Improving machine learning models and making them more secure by training on decentralized data.

  https://www.kdnuggets.com/2020/04/federated-learning-introduction.html

• Can Java Be Used for Machine Learning and Data Science?">Can Java Be Used for Machine Learning and Data Science?

  While Python and R have become favorites for building these programs, many organizations are turning to Java application development to meet their needs. Read on to see how, and why.

  https://www.kdnuggets.com/2020/04/java-used-machine-learning-data-science.html

• Peer Reviewing Data Science Projects">Peer Reviewing Data Science Projects

  In any technical development field, having other practitioners review your work before shipping code off to production is a valuable support tool to make sure your work is error-proof. Even through your preparation for the review, improvements might be discovered and then other issues that escaped your awareness can be spotted by outsiders. This peer scrutiny can also be applied to Data Science, and this article outlines a process that you can experiment with in your team.

  https://www.kdnuggets.com/2020/04/peer-reviewing-data-science-projects.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

• Evaluating Ray: Distributed Python for Massive Scalability

  If your team has started using ​Ray​ and you’re wondering what it is, this post is for you. If you’re wondering if Ray should be part of your technical strategy for Python-based applications, especially ML and AI, this post is for you.

  https://www.kdnuggets.com/2020/03/domino-ray-distributed-python-massive-scalability.html

• Exploring TensorFlow Quantum, Google’s New Framework for Creating Quantum Machine Learning Models

  TensorFlow Quantum allow data scientists to build machine learning models that work on quantum architectures.

  https://www.kdnuggets.com/2020/03/tensorflow-quantum-framework-quantum-machine-learning-models.html

• Nine lessons learned during my first year as a Data Scientist">Nine lessons learned during my first year as a Data Scientist

  What is it like to be a Data Scientist? There can be many hats to wear, and so many problems to solve that are fed with data, churned by data science, and guided by business results. Find out about lessons learned from one Data Scientist about how best to work and perform in the role.

  https://www.kdnuggets.com/2020/03/nine-lessons-first-year-data-scientist.html

• Time Series Classification Synthetic vs Real Financial Time Series">Time Series Classification Synthetic vs Real Financial Time Series

  This article discusses distinguishing between real financial time series and synthetic time series using XGBoost.

  https://www.kdnuggets.com/2020/03/time-series-classification-synthetic-real-financial-time-series.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 Most Useful Machine Learning Tools of 2020

  This articles outlines 5 sets of tools every lazy full-stack data scientist should use.

  https://www.kdnuggets.com/2020/03/most-useful-machine-learning-tools-2020.html

• Decision Boundary for a Series of Machine Learning Models

  I train a series of Machine Learning models using the iris dataset, construct synthetic data from the extreme points within the data and test a number of Machine Learning models in order to draw the decision boundaries from which the models make predictions in a 2D space, which is useful for illustrative purposes and understanding on how different Machine Learning models make predictions.

  https://www.kdnuggets.com/2020/03/decision-boundary-series-machine-learning-models.html

• Python Pandas For Data Discovery in 7 Simple Steps

  Just getting started with Python's Pandas library for data analysis? Or, ready for a quick refresher? These 7 steps will help you become familiar with its core features so you can begin exploring your data in no time.

  https://www.kdnuggets.com/2020/03/python-pandas-data-discovery.html

• 50 Must-Read Free Books For Every Data Scientist in 2020">50 Must-Read Free Books For Every Data Scientist in 2020

  In this article, we are listing down some excellent data science books which cover the wide variety of topics under Data Science.

  https://www.kdnuggets.com/2020/03/50-must-read-free-books-every-data-scientist-2020.html

• Free Mathematics Courses for Data Science & Machine Learning">Free Mathematics Courses for Data Science & Machine Learning

  It's no secret that mathematics is the foundation of data science. Here are a selection of courses to help increase your maths skills to excel in data science, machine learning, and beyond.

  https://www.kdnuggets.com/2020/02/free-mathematics-courses-data-science-machine-learning.html

• Microsoft Open Sources ZeRO and DeepSpeed: The Technologies Behind the Biggest Language Model in History

  The two efforts enable the training of deep learning models at massive scale.

  https://www.kdnuggets.com/2020/02/microsoft-open-sources-zero-deepspeed-language-model.html

• Sharing your machine learning models through a common API

  DEEPaaS API is a software component developed to expose machine learning models through a REST API. In this article we describe how to do it.

  https://www.kdnuggets.com/2020/02/sharing-machine-learning-models-common-api.html

• Basics of Audio File Processing in R

  This post provides basic information on audio processing using R as the programming language. It also walks through and understands some basics of sound and digital audio.

  https://www.kdnuggets.com/2020/02/basics-audio-file-processing-r.html

• Serverless Machine Learning with R on Cloud Run

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

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

• Uber Has Been Quietly Assembling One of the Most Impressive Open Source Deep Learning Stacks in the Market

  Many of the technologies used by Uber teams have been open sourced and received accolades from the machine learning community. Let’s look at some of my favorites.

  https://www.kdnuggets.com/2020/01/uber-quietly-assembling-impressive-open-source-deep-learning.html

• Top 7 Location Intelligence Companies in 2020

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

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

• I wanna be a data scientist, but… how?">I wanna be a data scientist, but… how?

  It’s easy to say "I wanna be a data scientist," but... where do you start? How much time is needed to be desired by companies? Do you need a Master’s degree? Do you need to know every mathematical concept ever derived? The journey might be long, but follow this plan to help you keep moving forward toward your career goal.

  https://www.kdnuggets.com/2020/01/wanna-be-data-scientist.html

• 10 Python Tips and Tricks You Should Learn Today">10 Python Tips and Tricks You Should Learn Today

  Check out this collection of 10 Python snippets that can be taken as a reference for your daily work.

  https://www.kdnuggets.com/2020/01/10-python-tips-tricks-learn-today.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

• 3 common data science career transitions, and how to make them happen

  Breaking into a career in Data Science can depend on where you start. See if you fit into one of these three categories of "newbies," and then find out how to make your professional transition into the field.

  https://www.kdnuggets.com/2020/01/3-common-data-science-career-transitions.html

• Beginner’s Guide to K-Nearest Neighbors in R: from Zero to Hero

  This post presents a pipeline of building a KNN model in R with various measurement metrics.

  https://www.kdnuggets.com/2020/01/beginners-guide-nearest-neighbors-r.html

• How HR Is Using Data Science and Analytics to Close the Gender Gap

  The gender gap can extend to the lack of equal representation in certain industries or career paths, and there's an extraordinarily long way to go before people will be on equal footing in the labor market. Human resources professionals can rely on data analytics to make progress.

  https://www.kdnuggets.com/2020/01/hr-data-science-analytics-gender-gap.html

• How To “Ultralearn” Data Science: deep understanding and experimentation, Part 4

  In this fourth and final part of the ultralearning data science series, it's time to take the final steps toward developing a deep understanding of the fundamentals and learning how to experiment -- the two aspects that are the ultimate keys to ultralearning.

  https://www.kdnuggets.com/2019/12/ultralearn-data-science-deep-understanding-experimentation-part4.html

• What is a Data Scientist Worth?">What is a Data Scientist Worth?

  What is the Salary of a Data Scientist in 2019? Let's have a look at some data to see how we can answer that question.

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

• The ravages of concept drift in stream learning applications and how to deal with it

  Stream data processing has gained progressive momentum with the arriving of new stream applications and big data scenarios. These streams of data evolve generally over time and may be occasionally affected by a change (concept drift). How to handle this change by using detection and adaptation mechanisms is crucial in many real-world systems.

  https://www.kdnuggets.com/2019/12/ravages-concept-drift-stream-learning-applications.html

• How To “Ultralearn” Data Science: removing distractions and finding focus, Part 2

  This second part in a series about how to "ultralearn" data science will guide you through several techniques to remove those distractions -- because your focus needs more focus.

  https://www.kdnuggets.com/2019/12/ultralearn-data-science-distractions-focus-part2.html

• Why software engineering processes and tools don’t work for machine learning

  While AI may be the new electricity significant challenges remain to realize AI potential. Here we examine why data scientists and teams can’t rely on software engineering tools and processes for machine learning.

  https://www.kdnuggets.com/2019/12/comet-software-engineering-machine-learning.html

• Enabling the Deep Learning Revolution

  Deep learning models are revolutionizing the business and technology world with jaw-dropping performances in one application area after another. Read this post on some of the numerous composite technologies which allow deep learning its complex nonlinearity.

  https://www.kdnuggets.com/2019/12/enabling-deep-learning-revolution.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

• Can Neural Networks Develop Attention? Google Thinks they Can

  Google recently published some work about modeling attention mechanisms in deep neural networks.

  https://www.kdnuggets.com/2019/11/neural-networks-develop-attention-google.html

• How to Visualize Data in Python (and R)

  Producing accessible data visualizations is a key data science skill. The following guidelines will help you create the best representations of your data using R and Python's Pandas library.

  https://www.kdnuggets.com/2019/11/visualize-data-python-and-r.html

• Facebook Adds This New Framework to It’s Reinforcement Learning Arsenal

  ReAgent is a new framework that streamlines the implementation of reasoning systems.

  https://www.kdnuggets.com/2019/11/facebook-adds-this-new-framework-reinforcement-learning-arsenal.html

• What is Data Science?

  Data Science is pitched as a modern and exciting job offering high satisfaction. Does its reality really live up to the hype? Here, we show what it's really like to work as a Data Scientist.

  https://www.kdnuggets.com/2019/11/what-is-data-science.html

• What is Machine Learning on Code?

  Not only can MLonCode help companies streamline their codebase and software delivery processes, but it also helps organizations better understand and manage their engineering talents.

  https://www.kdnuggets.com/2019/11/machine-learning-code-mloncode.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

• Introducing IceCAPS: Microsoft’s Framework for Advanced Conversation Modeling

  The new open source framework that brings multi-task learning to conversational agents.

  https://www.kdnuggets.com/2019/09/introducing-icecaps-microsofts-framework-advanced-conversation-modeling.html

• Scikit-Learn & More for Synthetic Dataset Generation for Machine Learning

  While mature algorithms and extensive open-source libraries are widely available for machine learning practitioners, sufficient data to apply these techniques remains a core challenge. Discover how to leverage scikit-learn and other tools to generate synthetic data appropriate for optimizing and fine-tuning your models.

  https://www.kdnuggets.com/2019/09/scikit-learn-synthetic-dataset.html

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

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

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

• TensorFlow 2.0: Dynamic, Readable, and Highly Extended

  With substantial changes coming with TensorFlow 2.0, and the release candidate version now available, learn more in this guide about the major updates and how to get started on the machine learning platform.

  https://www.kdnuggets.com/2019/08/tensorflow-20.html

• Artificial Intelligence vs. Machine Learning vs. Deep Learning: What is the Difference?

  Over the past few years, artificial intelligence continues to be one of the hottest topics. And in order to work effectively with it, you need to understand its constituent parts.

  https://www.kdnuggets.com/2019/08/artificial-intelligence-vs-machine-learning-vs-deep-learning-difference.html

• Understanding Decision Trees for Classification in Python

  This tutorial covers decision trees for classification also known as classification trees, including the anatomy of classification trees, how classification trees make predictions, using scikit-learn to make classification trees, and hyperparameter tuning.

  https://www.kdnuggets.com/2019/08/understanding-decision-trees-classification-python.html

• Deep Learning for NLP: Creating a Chatbot with Keras!">Deep Learning for NLP: Creating a Chatbot with Keras!

  Learn how to use Keras to build a Recurrent Neural Network and create a Chatbot! Who doesn’t like a friendly-robotic personal assistant?

  https://www.kdnuggets.com/2019/08/deep-learning-nlp-creating-chatbot-keras.html

• How to Become More Marketable as a Data Scientist">How to Become More Marketable as a Data Scientist

  As a data scientist, you are in high demand. So, how can you increase your marketability even more? Check out these current trends in skills most desired by employers in 2019.

  https://www.kdnuggets.com/2019/08/marketable-data-scientist.html

• Introduction to Image Segmentation with K-Means clustering

  Image segmentation is the classification of an image into different groups. Many kinds of research have been done in the area of image segmentation using clustering. In this article, we will explore using the K-Means clustering algorithm to read an image and cluster different regions of the image.

  https://www.kdnuggets.com/2019/08/introduction-image-segmentation-k-means-clustering.html

• Understanding Tensor Processing Units

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

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

• Top 13 Skills To Become a Rockstar Data Scientist">Top 13 Skills To Become a Rockstar Data Scientist

  Education, coding, SQL, big data platforms, storytelling and more. These are the 13 skills you need to master to become a rockstar data scientist.

  https://www.kdnuggets.com/2019/07/top-13-skills-become-rockstar-data-scientist.html

• Is SQL needed to be a data scientist?

  As long as there is ‘data’ in data scientist, Structured Query Language (or see-quel as we call it) will remain an important part of it. In this blog, let us explore data science and its relationship with SQL.

  https://www.kdnuggets.com/2019/07/sql-needed-data-scientist.html

• The Hackathon Guide for Aspiring Data Scientists">The Hackathon Guide for Aspiring Data Scientists

  This article is an overview of how to prepare for a hackathon as an aspiring data scientist, highlighting the 4 reasons why you should take part in one, along with a series of tips for participation.

  https://www.kdnuggets.com/2019/07/hackathon-guide-aspiring-data-scientists.html

• Introducing Gen: MIT’s New Language That Wants to be the TensorFlow of Programmable Inference">Introducing Gen: MIT’s New Language That Wants to be the TensorFlow of Programmable Inference

  Researchers from MIT recently unveiled a new probabilistic programming language named Gen, a language which allow researchers to write models and algorithms from multiple fields where AI techniques are applied without having to deal with equations or manually write high-performance code.

  https://www.kdnuggets.com/2019/07/introducing-gen-language-progammable-inference.html

• Top 10 Data Science Leaders You Should Follow">Top 10 Data Science Leaders You Should Follow

  If you’re in the data science field, I strongly encourage you to follow these giants— which I’ll list down in the section below — and be a part of our data science community to learn from the best and share your experience and knowledge.

  https://www.kdnuggets.com/2019/07/top-10-data-science-leaders.html

• An Overview of Human Pose Estimation with Deep Learning

  Human Pose Estimation is one of the main research areas in computer vision. The reason for its importance is the abundance of applications that can benefit from such a technology. Here's an introduction to the different techniques used in Human Pose Estimation based on Deep Learning.

  https://www.kdnuggets.com/2019/06/human-pose-estimation-deep-learning.html

• PySyft and the Emergence of Private Deep Learning

  PySyft is an open-source framework that enables secured, private computations in deep learning, by combining federated learning and differential privacy in a single programming model integrated into different deep learning frameworks such as PyTorch, Keras or TensorFlow.

  https://www.kdnuggets.com/2019/06/pysyft-emergence-deep-learning.html

• 10 Gradient Descent Optimisation Algorithms + Cheat Sheet

  Gradient descent is an optimization algorithm used for minimizing the cost function in various ML algorithms. Here are some common gradient descent optimisation algorithms used in the popular deep learning frameworks such as TensorFlow and Keras.

  https://www.kdnuggets.com/2019/06/gradient-descent-algorithms-cheat-sheet.html

• The Data Fabric for Machine Learning – Part 2: Building a Knowledge-Graph

  Before being able to develop a Data Fabric we need to build a Knowledge-Graph. In this article I’ll set up the basis on how to create it, in the next article we’ll go to the practice on how to do this.

  https://www.kdnuggets.com/2019/06/data-fabric-machine-learning-building-knowledge-graph.html

• Spark NLP: Getting Started With The World’s Most Widely Used NLP Library In The Enterprise"> Spark NLP: Getting Started With The World’s Most Widely Used NLP Library In The Enterprise

  The Spark NLP library has become a popular AI framework that delivers speed and scalability to your projects. Check out what's under the hood and learn about how to getting started leveraging Spark NLP from John Snow Labs.

  https://www.kdnuggets.com/2019/06/spark-nlp-getting-started-with-worlds-most-widely-used-nlp-library-enterprise.html

• Evolving Deep Neural Networks

  This article reviews how evolutionary algorithms have been proposed and tested as a competitive alternative to address a number of issues related to neural network design.

  https://www.kdnuggets.com/2019/06/evolving-deep-neural-networks.html

• If you’re a developer transitioning into data science, here are your best resources"> If you’re a developer transitioning into data science, here are your best resources

  This article will provide a background on the data scientist role and why your background might be a good fit for data science, plus tangible stepwise actions that you, as a developer, can take to ramp up on data science.

  https://www.kdnuggets.com/2019/06/developer-transitioning-data-science-best-resources.html

• 7 Steps to Mastering Intermediate Machine Learning with Python — 2019 Edition"> 7 Steps to Mastering Intermediate Machine Learning with Python — 2019 Edition

  This is the second part of this new learning path series for mastering machine learning with Python. Check out these 7 steps to help master intermediate machine learning with Python!

  https://www.kdnuggets.com/2019/06/7-steps-mastering-intermediate-machine-learning-python.html

• Understanding Backpropagation as Applied to LSTM

  Backpropagation is one of those topics that seem to confuse many once you move past feed-forward neural networks and progress to convolutional and recurrent neural networks. This article gives you and overall process to understanding back propagation by giving you the underlying principles of backpropagation.

  https://www.kdnuggets.com/2019/05/understanding-backpropagation-applied-lstm.html

• The Data Fabric for Machine Learning – Part 1">The Data Fabric for Machine Learning – Part 1

  How the new advances in semantics and the data fabric can help us be better at Machine Learning

  https://www.kdnuggets.com/2019/05/data-fabric-machine-learning-part-1.html

• 60+ useful graph visualization libraries">60+ useful graph visualization libraries

  We outline 60+ graph visualization libraries that allow users to build applications to display and interact with network representations of data.

  https://www.kdnuggets.com/2019/05/60-useful-graph-visualization-libraries.html

• What’s Going to Happen this Year in the Data World

  "If we wish to foresee the future of mathematics, our proper course is to study the history and present condition of the science." Henri Poncairé.

  https://www.kdnuggets.com/2019/05/whats-going-happen-this-year-data-world.html

• Best US/Canada Masters in Analytics, Business Analytics, Data Science

  In the final part of this series, we provide an updated list of our comprehensive, unbiased survey of graduate programs in Data Science and Analytics from across the US and Canada.

  https://www.kdnuggets.com/2019/05/best-masters-data-science-analytics-us-canada.html

• The 3 Biggest Mistakes on Learning Data Science">The 3 Biggest Mistakes on Learning Data Science

  Data science or whatever you want to call it is not just knowing some programming languages, math, statistics and have “domain knowledge” and here I show you why.

  https://www.kdnuggets.com/2019/05/biggest-mistakes-learning-data-science.html

• XGBoost Algorithm: Long May She Reign

  In recent years, XGBoost algorithm has gained enormous popularity in academic as well as business world. We outline some of the reasons behind this incredible success.

  https://www.kdnuggets.com/2019/05/xgboost-algorithm.html

• Which Deep Learning Framework is Growing Fastest?

  In September 2018, I compared all the major deep learning frameworks in terms of demand, usage, and popularity. TensorFlow was the champion of deep learning frameworks and PyTorch was the youngest framework. How has the landscape changed?

  https://www.kdnuggets.com/2019/05/which-deep-learning-framework-growing-fastest.html

• Generative Adversarial Networks – Key Milestones and State of the Art

  We provide an overview of Generative Adversarial Networks (GANs), discuss challenges in GANs learning, and examine two promising GANs: the RadialGAN, designed for numbers, and the StyleGAN, which does style transfer for images.

  https://www.kdnuggets.com/2019/04/future-generative-adversarial-networks.html