Search results for How to Invest

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• 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

• Is It Too Late to Learn AI?

  Have you missed the train on learning AI?

  https://www.kdnuggets.com/2021/03/too-late-learn-ai.html

• 3 Mathematical Laws Data Scientists Need To Know">3 Mathematical Laws Data Scientists Need To Know

  Machine learning and data science are founded on important mathematics in statistics and probability. A few interesting mathematical laws you should understand will especially help you perform better as a Data Scientist, including Benford's Law, the Law of Large Numbers, and Zipf's Law.

  https://www.kdnuggets.com/2021/03/3-mathematical-laws.html

• The Difficulty of Graph Anonymisation

  Lessons from network science and the difficulty of graph anonymization. A data scientist's take on the difficultly of striking a balance between privacy and utility in anonymizing connected data.

  https://www.kdnuggets.com/2021/02/difficulty-graph-anonymisation.html

• Data Observability, Part II: How to Build Your Own Data Quality Monitors Using SQL

  Using schema and lineage to understand the root cause of your data anomalies.

  https://www.kdnuggets.com/2021/02/data-observability-part-2-build-data-quality-monitors-sql.html

• An overview of synthetic data types and generation methods

  Synthetic data can be used to test new products and services, validate models, or test performances because it mimics the statistical property of production data. Today you'll find different types of structured and unstructured synthetic data.

  https://www.kdnuggets.com/2021/02/overview-synthetic-data-types-generation-methods.html

• Powerful Exploratory Data Analysis in just two lines of code">Powerful Exploratory Data Analysis in just two lines of code

  EDA is a fundamental early process for any Data Science investigation. Typical approaches for visualization and exploration are powerful, but can be cumbersome for getting to the heart of your data. Now, you can get to know your data much faster with only a few lines of code... and it might even be fun!

  https://www.kdnuggets.com/2021/02/powerful-exploratory-data-analysis-sweetviz.html

• Feature Store as a Foundation for Machine Learning

  With so many organizations now taking the leap into building production-level machine learning models, many lessons learned are coming to light about the supporting infrastructure. For a variety of important types of use cases, maintaining a centralized feature store is essential for higher ROI and faster delivery to market. In this review, the current feature store landscape is described, and you can learn how to architect one into your MLOps pipeline.

  https://www.kdnuggets.com/2021/02/feature-store-foundation-machine-learning.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

• My machine learning model does not learn. What should I do?

  This article presents 7 hints on how to get out of the quicksand.

  https://www.kdnuggets.com/2021/02/machine-learning-model-not-learn.html

• The Best Data Science Project to Have in Your Portfolio">The Best Data Science Project to Have in Your Portfolio

  If you are trying to find your first path into a Data Science career, then demonstrating the quality of your skills can be the greatest hurdle. While many standard projects exist for anyone to complete, creating an original data-driven project that attempts to solve some challenge is worth so much more. A good Data Scientist is one that can solve data-related questions, and a great Data Scientist poses original data-related questions and then solves.

  https://www.kdnuggets.com/2021/02/best-data-science-project-portfolio.html

• Beyond the Nash Equilibrium: DeepMind Clever Strategy to Solve Asymmetric Games

  The method expands the concept of a Nash equilibrium by decomposing an asymmetric game into multiple symmetric games.

  https://www.kdnuggets.com/2021/02/beyond-nash-equilibrium-deepmind-solve-asymmetric-games.html

• What is Graph Theory, and Why Should You Care?

  Go from graph theory to path optimization.

  https://www.kdnuggets.com/2021/01/graph-theory-why-care.html

• Machine learning is going real-time

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

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

• Cloud Computing, Data Science and ML Trends in 2020–2022: The battle of giants">Cloud Computing, Data Science and ML Trends in 2020–2022: The battle of giants

  Kaggle’s survey of ‘State of Data Science and Machine Learning 2020’ covers a lot of diverse topics. In this post, we are going to look at the popularity of cloud computing platforms and products among the data science and ML professionals participated in the survey.

  https://www.kdnuggets.com/2021/01/cloud-computing-data-science-ml-trends-2020-2022-battle-giants.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

• Creating Good Meaningful Plots: Some Principles

  Hera are some thought starters to help you create meaningful plots.

  https://www.kdnuggets.com/2021/01/creating-good-meaningful-plots-principles.html

• 5 Tools for Effortless Data Science

  The sixth tool is coffee.

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

• Top 10 Computer Vision Papers 2020">Top 10 Computer Vision Papers 2020

  The top 10 computer vision papers in 2020 with video demos, articles, code, and paper reference.

  https://www.kdnuggets.com/2021/01/top-10-computer-vision-papers-2020.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

• 10 Underappreciated Python Packages for Machine Learning Practitioners">10 Underappreciated Python Packages for Machine Learning Practitioners

  Here are 10 underappreciated Python packages covering neural architecture design, calibration, UI creation and dissemination.

  https://www.kdnuggets.com/2021/01/10-underappreciated-python-packages-machine-learning-practitioners.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

• 2020: A Year Full of Amazing AI Papers — A Review

  So much happened in the world during 2020 that it may have been easy to miss the great progress in the world of AI. To catch you up quickly, check out this curated list of the latest breakthroughs in AI by release date, along with a video explanation, link to an in-depth article, and code.

  https://www.kdnuggets.com/2020/12/2020-amazing-ai-papers.html

• Data Catalogs Are Dead; Long Live Data Discovery

  Why data catalogs aren’t meeting the needs of the modern data stack, and how a new approach – data discovery – is needed to better facilitate metadata management and data reliability.

  https://www.kdnuggets.com/2020/12/data-catalogs-dead-long-live-data-discovery.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

• Navigate the road to Responsible AI

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

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

• ebook: Fundamentals for Efficient ML Monitoring

  We've gathered best practices for data science and engineering teams to create an efficient framework to monitor ML models. This ebook provides a framework for anyone who has an interest in building, testing, and implementing a robust monitoring strategy in their organization or elsewhere.

  https://www.kdnuggets.com/2020/12/superwise-ebook-fundamentals-ml-monitoring.html

• 8 Places for Data Professionals to Find Datasets

  Here is a curated list of sites and resources invaluable for data professionals to acquire practice datasets.

  https://www.kdnuggets.com/2020/12/8-places-data-professionals-find-datasets.html

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

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

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

• How to Clean Text Data at the Command Line

  A basic tutorial about cleaning data using command-line tools: tr, grep, sort, uniq, sort, awk, sed, and csvlook.

  https://www.kdnuggets.com/2020/12/clean-text-data-command-line.html

• Applications of Data Science and Business Analytics

  In recent times, a large number of businesses have begun realising the potential of Data Science. Business analytics and data science applications are far and wide. So let us have a look at them in detail.

  https://www.kdnuggets.com/2020/12/greatlearning-applications-data-science-business-analytics.html

• State of Data Science and Machine Learning 2020: 3 Key Findings">State of Data Science and Machine Learning 2020: 3 Key Findings

  Kaggle recently released its State of Data Science and Machine Learning report for 2020, based on compiled results of its annual survey. Read about 3 key findings in the report here.

  https://www.kdnuggets.com/2020/12/kaggle-survey-2020-data-science-machine-learning.html

• A Rising Library Beating Pandas in Performance">A Rising Library Beating Pandas in Performance

  This article compares the performance of the well-known pandas library with pypolars, a rising DataFrame library written in Rust. See how they compare.

  https://www.kdnuggets.com/2020/12/rising-library-beating-pandas-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

• AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2020 and Key Trends for 2021">AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2020 and Key Trends for 2021

  2020 is finally coming to a close. While likely not to register as anyone's favorite year, 2020 did have some noteworthy advancements in our field, and 2021 promises some important key trends to look forward to. As has become a year-end tradition, our collection of experts have once again contributed their thoughts. Read on to find out more.

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

• Remembering Pluribus: The Techniques that Facebook Used to Master World’s Most Difficult Poker Game

  Pluribus used incredibly simple AI methods to set new records in six-player no-limit Texas Hold’em poker. How did it do it?

  https://www.kdnuggets.com/2020/12/remembering-pluribus-facebook-master-difficult-poker-game.html

• Data science certification – why it is important and where to get it?

  Data science jobs are one of most sought after and in-demand jobs in the IT industry right now. In order to get into this field and get these data science jobs, certification is needed and that is widely discussed below.

  https://www.kdnuggets.com/2020/11/greatlearning-data-science-certification.html

• How Machine Learning Works for Social Good

  We often discuss applying data science and machine learning techniques in term so of how they help your organization or business goals. But, these algorithms aren't limited to only increasing the bottom line. Developing new applications that leverage the predictive power of AI to benefit society and those communities in need is an equally valuable endeavor for Data Scientists that will further expand the positive impact of machine learning to the world.

  https://www.kdnuggets.com/2020/11/machine-learning-social-good.html

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

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

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

• Hypothesis Vetting: The Most Important Skill Every Successful Data Scientist Needs

  A well-thought hypothesis sets the direction and plan for a Data Science project. Accordingly, a hypothesis is the most important item for evaluating whether a Data Science project will be successful.

  https://www.kdnuggets.com/2020/11/hypothesis-vetting-most-important-skill-every-successful-data-scientist-needs.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

• Free From MIT: Intro to Computational Thinking with Julia

  Introduction to Computational Thinking with Julia, with Applications to Modeling the COVID-19 Pandemic is another freely-available offering from MIT's Open Courseware.

  https://www.kdnuggets.com/2020/11/free-mit-intro-computational-thinking-julia.html

• Six Ethical Quandaries of Predictive Policing

  When predictive machine learning models are applied to real-life scenarios, especially those that directly impact humans, such as cancer detection and other medical-related applications, the risks involved with incorrect predictions carry very high stakes. These risks are also prominent in how machine learning is applied in law enforcement, and serious ethical questions must be considered.

  https://www.kdnuggets.com/2020/11/six-ethical-quandaries-predictive-policing.html

• 10 Principles of Practical Statistical Reasoning

  Practical Statistical Reasoning is a term that covers the nature and objective of applied statistics/data science, principles common to all applications, and practical steps/questions for better conclusions. The following principles have helped me become more efficient with my analyses and clearer in my conclusions.

  https://www.kdnuggets.com/2020/11/10-principles-practical-statistical-reasoning.html

• The Missing Teams For Data Scientists

  Still today, too large a percent of data science projects fail, many of which can be attributed to the impacts of how hard missing data teams hit the data science team. Advocating for the missing data engineering and operations components to your team will make your professional life easier and more productive.

  https://www.kdnuggets.com/2020/11/missing-teams-data-scientists.html

• How Automation Is Improving the Role of Data Scientists

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

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

• 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

• 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

• The Ethics of AI

  Marketing scientist Kevin Gray asks Dr. Anna Farzindar of the University of Southern California about a very important subject - the ethics of AI.

  https://www.kdnuggets.com/2020/10/ethics-ai-qa-farzindar.html

• Deep Learning for Virtual Try On Clothes – Challenges and Opportunities

  Learn about the experiments by MobiDev for transferring 2D clothing items onto the image of a person. As part of their efforts to bring AR and AI technologies into virtual fitting room development, they review the deep learning algorithms and architecture under development and the current state of results.

  https://www.kdnuggets.com/2020/10/deep-learning-virtual-try-clothes.html

• The Future of Fake News

  Let's talk about misleading communications in the digital era.

  https://www.kdnuggets.com/2020/10/future-fake-news.html

• Annotated Machine Learning Research Papers">Annotated Machine Learning Research Papers

  Check out this collection of annotated machine learning research papers, and no longer fear their reading.

  https://www.kdnuggets.com/2020/10/annotated-machine-learning-research-papers.html

• 6 Lessons Learned in 6 Months as a Data Scientist

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

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

• Your Guide to Linear Regression Models

  This article explains linear regression and how to program linear regression models in Python.

  https://www.kdnuggets.com/2020/10/guide-linear-regression-models.html

• AI in Healthcare: A review of innovative startups

  The AI innovation in healthcare has been overwhelming with the Global Healthcare AI Market accounting for $0.95 billion in 2017, and is expected to reach $19.25 billion by 2026. What drives this vibrant growth?

  https://www.kdnuggets.com/2020/09/ai-healthcare-review-innovative-startups.html

• Missing Value Imputation – A Review

  Detecting and handling missing values in the correct way is important, as they can impact the results of the analysis, and there are algorithms that can’t handle them. So what is the correct way?

  https://www.kdnuggets.com/2020/09/missing-value-imputation-review.html

• The Online Courses You Must Take to be a Better Data Scientist

  These select courses have proved to be precious online resources which helped make the author a better data scientist today.

  https://www.kdnuggets.com/2020/09/online-courses-better-data-scientist.html

• Artificial Intelligence for Precision Medicine and Better Healthcare

  In this article, we will focus on various machine learning, deep learning models, and applications of AI which can pave the way for a new data-centric era of discovery in healthcare.

  https://www.kdnuggets.com/2020/09/artificial-intelligence-precision-medicine-better-healthcare.html

• MathWorks Deep learning workflow: tips, tricks, and often forgotten steps

  Getting started in deep learning – and adopting an organized, sustainable, and reproducible workflow – can be challenging. This blog post will share some tips and tricks to help you develop a systematic, effective, attainable, and scalable deep learning workflow as you experiment with different deep learning models, datasets, and applications.

  https://www.kdnuggets.com/2020/09/mathworks-deep-learning-workflow.html

• How to Effectively Obtain Consumer Insights in a Data Overload Era

  Everybody knows how important is understanding your customer, but how to do that in an era of Information Overload?

  https://www.kdnuggets.com/2020/09/effectively-obtain-consumer-insights-data-overload-era.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

• Data Scientists think data is their #1 problem. Here’s why they’re wrong.

  We tend to think it's all about the data. However, for real data science projects at real organizations in real life, there are more fundamental aspects to consider to do data science right.

  https://www.kdnuggets.com/2020/09/data-scientist-data-problem-wrong.html

• Design of Experiments in Data Science

  Read this overview of the process of designing experiments for collecting data.

  https://www.kdnuggets.com/2020/09/design-experiments-data-science.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

• Showcasing the Benefits of Software Optimizations for AI Workloads on Intel® Xeon® Scalable Platforms

  The focus of this blog is to bring to light that continued software optimizations can boost performance not only for the latest platforms, but also for the current install base from prior generations. This means customers can continue to extract value from their current platform investments.

  https://www.kdnuggets.com/2020/09/showcasing-benefits-software-optimizations-ai-workloads-intel.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

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

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

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

• 3D Human Pose Estimation Experiments and Analysis

  In this article, we explore how 3D human pose estimation works based on our research and experiments, which were part of the analysis of applying human pose estimation in AI fitness coach applications.

  https://www.kdnuggets.com/2020/08/3d-human-pose-estimation-experiments-analysis.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

• Hypothesis Test for Real Problems

  Hypothesis tests are significant for evaluating answers to questions concerning samples of data.

  https://www.kdnuggets.com/2020/08/hypothesis-test-real-problems.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

• 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

• The Uncommon Data Science Job Guide

  With the job landscape in Data Science becoming hyper-competitive, there are clear strategies you can consider to find your way to snagging a position in the field.

  https://www.kdnuggets.com/2020/08/data-science-job-guide.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

• Scaling Computer Vision Models with Dataflow

  Scaling Machine Learning models is hard and expensive. We will shortly introduce the Google Cloud service Dataflow, and how it can be used to run predictions on millions of images in a serverless way.

  https://www.kdnuggets.com/2020/07/scaling-computer-vision-models-dataflow.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

• Essential Resources to Learn Bayesian Statistics">Essential Resources to Learn Bayesian Statistics

  If you are interesting in becoming better at statistics and machine learning, then some time should be invested in diving deeper into Bayesian Statistics. While the topic is more advanced, applying these fundamentals to your work will advance your understanding and success as an ML expert.

  https://www.kdnuggets.com/2020/07/essential-resources-learn-bayesian-statistics.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

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

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

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

• What I learned from looking at 200 machine learning tools

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

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

• The Bitter Lesson of Machine Learning">The Bitter Lesson of Machine Learning

  Since that renowned conference at Dartmouth College in 1956, AI research has experienced many crests and troughs of progress through the years. From the many lessons learned during this time, some have needed to be re-learned -- repeatedly -- and the most important of which has also been the most difficult to accept by many researchers.

  https://www.kdnuggets.com/2020/07/bitter-lesson-machine-learning.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

• Deep Learning in Finance: Is This The Future of the Financial Industry?

  Get a handle on how deep learning is affecting the finance industry, and identify resources to further this understanding and increase your knowledge of the various aspects.

  https://www.kdnuggets.com/2020/07/deep-learning-finance-future-financial-industry.html

• Pull and Analyze Financial Data Using a Simple Python Package

  We demonstrate a simple Python script/package to help you pull financial data (all the important metrics and ratios that you can think of) and plot them.

  https://www.kdnuggets.com/2020/07/pull-analyze-financial-data-simple-python-package.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

• Learning by Forgetting: Deep Neural Networks and the Jennifer Aniston Neuron">Learning by Forgetting: Deep Neural Networks and the Jennifer Aniston Neuron

  DeepMind’s research shows how to understand the role of individual neurons in a neural network.

  https://www.kdnuggets.com/2020/06/learning-forgetting-deep-neural-networks-jennifer-aniston.html

• Free Economics & Finance Courses for Data Scientists

  Here is a selection of courses for those interested in diversifying their domain knowledge into the related realms of economics and finance, with the goal of being able to apply your data science skills to these domains.

  https://www.kdnuggets.com/2020/06/free-economics-finance-courses-data-scientists.html

• Tools to Spot Deepfakes and AI-Generated Text

  The technologies that generate deepfake content is at the forefront of manipulating humans. While the research developing these algorithms is fascinating and will lead to powerful tools that enhance the way people create and work, in the wrong hands, these same tools drive misinformation at a scale we can't yet imagine. Stopping these bad actors using awesome tools is in your hands.

  https://www.kdnuggets.com/2020/06/dont-click-this-how-spot-deepfakes.html

• Five Cognitive Biases In Data Science (And how to avoid them)">Five Cognitive Biases In Data Science (And how to avoid them)

  Everyone is prey to cognitive biases that skew thinking, but data scientists must prevent them from spoiling their work. Learn more about five biases that can all too easily make your seemingly objective work become surprisingly subjective.

  https://www.kdnuggets.com/2020/06/five-cognitive-biases-data-science.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

• How to make AI/Machine Learning models resilient during COVID-19 crisis

  COVID-19-driven concept shift has created concern over the usage of AI/ML to continue to drive business value following cases of inaccurate outputs and misleading results from a variety of fields. Data Science teams must invest effort in post-model tracking and management as well as deploy an agility in the AI/ML process to curb problems related to concept shift.

  https://www.kdnuggets.com/2020/06/ai-ml-models-resilient-covid-19-crisis.html

• GPT-3, a giant step for Deep Learning and NLP?

  Recently, OpenAI announced a new successor to their language model, GPT-3, that is now the largest model trained so far with 175 billion parameters. Training a language model this large has its merits and limitations, so this article covers some of its most interesting and important aspects.

  https://www.kdnuggets.com/2020/06/gpt-3-deep-learning-nlp.html

• Why Do AI Systems Need Human Intervention to Work Well?

  All is not well with artificial intelligence-based systems during the coronavirus pandemic. No, the virus does not impact AI – however, it does impact humans, without whom AI and ML systems cannot function properly. Surprised?

  https://www.kdnuggets.com/2020/06/ai-systems-need-human-intervention.html

• Deep Learning for Detecting Pneumonia from X-ray Images">Deep Learning for Detecting Pneumonia from X-ray Images

  This article covers an end to end pipeline for pneumonia detection from X-ray images.

  https://www.kdnuggets.com/2020/06/deep-learning-detecting-pneumonia-x-ray-images.html

• 3 Key Data Science Questions to Ask Your Big Data

  The process of understanding your data begins by asking 3 questions at the highest level, and then iteratively asking hundreds of cascading questions to get deeper insights.

  https://www.kdnuggets.com/2020/06/3-key-data-science-questions.html

• Four Ways to Apply NLP in Financial Services

  Natural language processing (NLP) is increasingly used to review unstructured content or spot trends in markets. How is Refinitiv Labs applying NLP in financial services to meet challenges around investment decision-making and risk management?

  https://www.kdnuggets.com/2020/06/four-ways-apply-nlp-financial-services.html

• Deep Learning for Coders with fastai and PyTorch: The Free eBook">Deep Learning for Coders with fastai and PyTorch: The Free eBook

  If you are interested in a top-down, example-driven book on deep learning, check out the draft of the upcoming Deep Learning for Coders with fastai & PyTorch from fast.ai team.

  https://www.kdnuggets.com/2020/06/fastai-book-free-ebook.html

• How to Think Like a Data Scientist">How to Think Like a Data Scientist

  So what does it take to become a data scientist? For some pointers on the skills for success, I interviewed Ben Chu, who is a Senior Data Scientist at Refinitiv Labs.

  https://www.kdnuggets.com/2020/05/think-like-data-scientist-data-analyst.html

• 5 Machine Learning Papers on Face Recognition

  This article will highlight some of that research and introduce five machine learning papers on face recognition.

  https://www.kdnuggets.com/2020/05/5-machine-learning-papers-face-recognition.html

• Dimensionality Reduction with Principal Component Analysis (PCA)

  This article focuses on design principles of the PCA algorithm for dimensionality reduction and its implementation in Python from scratch.

  https://www.kdnuggets.com/2020/05/dimensionality-reduction-principal-component-analysis.html

• Spotting Controversy with NLP

  In this article, I’ll introduce you to a hot-topic in financial services and describe how a leading data provider is using data science and NLP to streamline how they find insights in unstructured data.

  https://www.kdnuggets.com/2020/05/spotting-controversy-nlp.html

• Looking Normal(ly Distributed)

  This article investigates when some probability distributions look normal "enough" for a statistical test.

  https://www.kdnuggets.com/2020/05/looking-normally-distributed.html

• Explaining “Blackbox” Machine Learning Models: Practical Application of SHAP

  Train a "blackbox" GBM model on a real dataset and make it explainable with SHAP.

  https://www.kdnuggets.com/2020/05/explaining-blackbox-machine-learning-models-practical-application-shap.html

• Best Coronavirus Projections, Predictions, Dashboards and Data Resources

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

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

• 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

• LSTM for time series prediction

  Learn how to develop a LSTM neural network with PyTorch on trading data to predict future prices by mimicking actual values of the time series data.

  https://www.kdnuggets.com/2020/04/lstm-time-series-prediction.html

• Should Data Scientists Model COVID19 and other Biological Events">Should Data Scientists Model COVID19 and other Biological Events

  Biostatisticians use statistical techniques that your current everyday data scientists have probably never heard of. This is a great example where lack of domain knowledge exposes you as someone that does not know what they are doing and are merely hopping on a trend.

  https://www.kdnuggets.com/2020/04/data-scientists-model-covid19-biological-events.html

• 4 Realistic Career Options for Data Scientists

  It’s almost 10 years since "Data Science" became mainstream. We ask less about how to get into Data Science, but wonder "what’s next?" This article includes insights on four non-trivial, but practical, options and their pitfalls.

  https://www.kdnuggets.com/2020/04/4-career-options-data-scientists.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

• Top Process Mining Software Companies, Updated

  Understanding the real business processes of a company through analysis of its information systems can guide digital transformations. Here, the top 10 process mining software companies are reviewed that can assist businesses in process optimizations through unique insights of business systems.

  https://www.kdnuggets.com/2020/04/process-mining-software-companies.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

• How Deep Learning is Accelerating Drug Discovery in Pharmaceuticals">How Deep Learning is Accelerating Drug Discovery in Pharmaceuticals

  The goal of this essay is to discuss meaningful machine learning progress in the real-world application of drug discovery. There’s even a solid chance of the deep learning approach to drug discovery changing lives for the better doing meaningful good in the world.

  https://www.kdnuggets.com/2020/04/deep-learning-accelerating-drug-discovery-pharmaceuticals.html

• 2 Things You Need to Know about Reinforcement Learning – Computational Efficiency and Sample Efficiency

  Experimenting with different strategies for a reinforcement learning model is crucial to discovering the best approach for your application. However, where you land can have significant impact on your system's energy consumption that could cause you to think again about the efficiency of your computations.

  https://www.kdnuggets.com/2020/04/2-things-reinforcement-learning.html

• Best Free Epidemiology Courses for Data Scientists">Best Free Epidemiology Courses for Data Scientists

  Are you interested in knowing more about epidemiology, the field which studies the spread and distribution of diseases? This article collects some free courses which are intended to help you do just that.

  https://www.kdnuggets.com/2020/04/epidemiology-data-scientists.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

• Why you should NOT use MS MARCO to evaluate semantic search

  If we want to investigate the power and limitations of semantic vectors (pre-trained or not), we should ideally prioritize datasets that are less biased towards term-matching signals. This piece shows that the MS MARCO dataset is more biased towards those signals than we expected and that the same issues are likely present in many other datasets due to similar data collection designs.

  https://www.kdnuggets.com/2020/04/ms-marco-evaluate-semantic-search.html

• Introducing MIDAS: A New Baseline for Anomaly Detection in Graphs">Introducing MIDAS: A New Baseline for Anomaly Detection in Graphs

  From network security to financial fraud, anomaly detection helps protect businesses, individuals, and online communities. To help improve anomaly detection, researchers have developed a new approach called MIDAS.

  https://www.kdnuggets.com/2020/04/midas-new-baseline-anomaly-detection-graphs.html

• Research into 1,001 Data Scientist LinkedIn Profiles, the latest">Research into 1,001 Data Scientist LinkedIn Profiles, the latest

  What makes a data scientist today? Consider this review of data collected from three years worth of data scientist LinkedIn profiles to gain insight into how this important new career path is shaping up.

  https://www.kdnuggets.com/2020/03/1001-data-scientist-linkedin-profiles-latest.html

• Deep Learning Breakthrough: a sub-linear deep learning algorithm that does not need a GPU?

  Deep Learning sits at the forefront of many important advances underway in machine learning. With backpropagation being a primary training method, its computational inefficiencies require sophisticated hardware, such as GPUs. Learn about this recent breakthrough algorithmic advancement with improvements to the backpropgation calculations on a CPU that outperforms large neural network training with a GPU.

  https://www.kdnuggets.com/2020/03/deep-learning-breakthrough-sub-linear-algorithm-no-gpu.html

• Top AI Resources – Directory for Remote Learning

  Whether you are just learning Data Science, a current professional, or just interested, it's crucial to keep the mind stimulated and stay current. With conferences, schools, and travel largely canceled because of #coronavirus, these remote resources will help you stay engaged.

  https://www.kdnuggets.com/2020/03/top-ai-resources-remote-learning.html

• A Comprehensive Data Repository for Fake Health News Detection

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

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

• Skynet Is Real: The History and Future of Factories With No Workers

  Let’s see whether robots will become "grave diggers" of the proletariat, what do we lack to get total automation, and what compromises exist.

  https://www.kdnuggets.com/2020/03/skynet-real-history-future-factories-no-workers.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

• Software Interfaces for Machine Learning Deployment

  While building a machine learning model might be the fun part, it won't do much for anyone else unless it can be deployed into a production environment. How to implement machine learning deployments is a special challenge with differences from traditional software engineering, and this post examines a fundamental first step -- how to create software interfaces so you can develop deployments that are automated and repeatable.

  https://www.kdnuggets.com/2020/03/software-interfaces-machine-learning-deployment.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

• A Crash Course in Game Theory for Machine Learning: Classic and New Ideas

  Game theory is experiencing a renaissance driven by the evolution of AI. What are some classic and new ideas that data scientists should be aware of.

  https://www.kdnuggets.com/2020/03/crash-course-game-theory-machine-learning.html

• Analyzing GDPR Fines – who are largest violators?

  Fines from the GDPR have been rolling in since its inception in 2018. This article investigates who are the largest penalty recipients by country, the amounts, and private individuals.

  https://www.kdnuggets.com/2020/03/analyzing-gdpr-fines.html

• Trends in Machine Learning in 2020

  Many industries realize the potential of Machine Learning and are incorporating it as a core technology. Progress and new applications of these tools are moving quickly in the field, and we discuss expected upcoming trends in Machine Learning for 2020.

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