Search results for learn R

Found 5516 documents, 5944 searched:

• How to Become a Machine Learning Engineer

  A machine learning engineer is a programmer proficient in building and designing software to automate predictive models. They have a deeper focus on computer science, compared to data scientists.

  https://www.kdnuggets.com/2022/05/become-machine-learning-engineer.html

• Data Science, Statistics and Machine Learning Dictionary

  Check out this curated list of the most used data science terminology and get a leg up on your learning.

  https://www.kdnuggets.com/2022/05/data-science-statistics-machine-learning-dictionary.html

• KDnuggets News, May 25: The 6 Python Machine Learning Tools Every Data Scientist Should Know About; The Complete Collection of Data Science Books

  The 6 Python Machine Learning Tools Every Data Scientist Should Know About; The Complete Collection of Data Science Books - Part 1; Finding the Best IDE Software; 5 Ways to Double Your Income with Data Science; Operationalizing Machine Learning from PoC to Production

  https://www.kdnuggets.com/2022/n21.html

• Machine Learning Is Not Like Your Brain Part Two: Perceptrons vs Neurons

  An ML system requiring thousands of tagged samples is fundamentally different from the mind of a child, which can learn from just a few experiences of untagged data.

  https://www.kdnuggets.com/2022/05/machine-learning-like-brain-part-two-perceptrons-neurons.html

• Operationalizing Machine Learning from PoC to Production

  Most companies haven’t seen ROI from machine learning since the benefit is only realized when the models are in production. Here’s how to make sure your ML project works.

  https://www.kdnuggets.com/2022/05/operationalizing-machine-learning-poc-production.html

• The 6 Python Machine Learning Tools Every Data Scientist Should Know About

  Let's look at six must-have tools every data scientist should use.

  https://www.kdnuggets.com/2022/05/6-python-machine-learning-tools-every-data-scientist-know.html

• KDnuggets News, May 18: 5 Free Hosting Platform For Machine Learning Applications; Data Mesh Architecture: Reimagining Data Management

  5 Free Hosting Platform For Machine Learning Applications; Data Mesh Architecture: Reimagining Data Management; Popular Machine Learning Algorithms; Reinforcement Learning for Newbies ; Deep Learning For Compliance Checks: What's New?

  https://www.kdnuggets.com/2022/n20.html

• HuggingFace Has Launched a Free Deep Reinforcement Learning Course

  Hugging Face has released a free course on Deep RL. It is self-paced and shares a lot of pointers on theory, tutorials, and hands-on guides.

  https://www.kdnuggets.com/2022/05/huggingface-launched-free-deep-reinforcement-learning-course.html

• Popular Machine Learning Algorithms

  This guide will help aspiring data scientists and machine learning engineers gain better knowledge and experience. I will list different types of machine learning algorithms, which can be used with both Python and R.

  https://www.kdnuggets.com/2022/05/popular-machine-learning-algorithms.html

• Reinforcement Learning for Newbies

  A simple guide to reinforcement learning for a complete beginner. The blog includes definitions with examples, real-life applications, key concepts, and various types of learning resources.

  https://www.kdnuggets.com/2022/05/reinforcement-learning-newbies.html

• Deep Learning For Compliance Checks: What’s New?

  By implementing the different NLP techniques into the production processes, compliance departments can maintain detailed checks and keep up with regulator demands.

  https://www.kdnuggets.com/2022/05/deep-learning-compliance-checks-new.html

• 5 Free Hosting Platform For Machine Learning Applications

  Learn about the free and easy-to-deploy hosting platform for your machine learning projects.

  https://www.kdnuggets.com/2022/05/5-free-hosting-platform-machine-learning-applications.html

• Quick Data Science Tips and Tricks to Learn SAS

  How To Tutorials with SAS data scientists and analytics instructors.

  https://www.kdnuggets.com/2022/05/sas-quick-data-science-tips-tricks-learn.html

• Machine Learning’s Sweet Spot: Pure Approaches in NLP and Document Analysis

  While it is true that Machine Learning today isn’t ready for prime time in many business cases that revolve around Document Analysis, there are indeed scenarios where a pure ML approach can be considered.

  https://www.kdnuggets.com/2022/05/machine-learning-sweet-spot-pure-approaches-nlp-document-analysis.html

• Machine Learning Key Terms, Explained

  Read this overview of 12 important machine learning concepts, presented in a no frills, straightforward definition style.

  https://www.kdnuggets.com/2016/05/machine-learning-key-terms-explained.html

• Machine Learning Is Not Like Your Brain Part One: Neurons Are Slow, Slow, Slow

  Artificial intelligence is not all that intelligent. While today’s AI can do some extraordinary things, the functionality underlying its accomplishments has very little to do with the way in which a human brain works to achieve the same tasks.

  https://www.kdnuggets.com/2022/04/machine-learning-like-brain-part-one-neurons-slow-slow-slow.html

• KDnuggets News, May 4: 9 Free Harvard Courses to Learn Data Science; 15 Python Coding Interview Questions You Must Know For Data Science

  9 Free Harvard Courses to Learn Data Science in 2022; 15 Python Coding Interview Questions You Must Know For Data Science; Best Data Science Career Tracks of 2022; 6 Highest Paying Companies for Data Scientists; Why You Need To Learn Python In 2022

  https://www.kdnuggets.com/2022/n18.html

• Top 10 Machine Learning Demos: Hugging Face Spaces Edition

  Hugging Face Spaces allows you to have an interactive experience with the machine learning models, and we will be discovering the best application to get some inspiration.

  https://www.kdnuggets.com/2022/05/top-10-machine-learning-demos-hugging-face-spaces-edition.html

• Why You Need To Learn Python In 2022

  If you don’t already know a programming language, or if you’re deciding to choose another language, have a read and see if Python is for you.

  https://www.kdnuggets.com/2022/04/need-learn-python-2022.html

• KDnuggets News, April 27: A Brief Introduction to Papers With Code; Machine Learning Books You Need To Read In 2022

  A Brief Introduction to Papers With Code; Machine Learning Books You Need To Read In 2022; Building a Scalable ETL with SQL + Python; 7 Steps to Mastering SQL for Data Science; Top Data Science Projects to Build Your Skills

  https://www.kdnuggets.com/2022/n17.html

• Getting Deep Learning working in the wild: A Data-Centric Course

  Data-centric learning resources are somewhat scattered today, and that’s why we developed a new Data Centric Deep Learning course on the co:rise education platform. It is an introduction to a set of approaches and best practices, for people who are trying to do deep learning in the wild.

  https://www.kdnuggets.com/2022/04/corise-deep-learning-wild-data-centric-course.html

• A Simple Guide to Machine Learning Visualisations

  Create simple, effective machine learning plots with Yellowbrick

  https://www.kdnuggets.com/2022/04/simple-guide-machine-learning-visualisations.html

• Machine Learning Books You Need To Read In 2022

  I have a list of Machine Learning books you need to read in 2022; beginner, intermediate, expert, and for everybody.

  https://www.kdnuggets.com/2022/04/machine-learning-books-need-read-2022.html

• KDnuggets News 22:n16, Apr 20: Top YouTube Channels for Learning Data Science; Data Visualization in Python with Seaborn

  Top YouTube Channels for Learning Data Science; Data Visualization in Python with Seaborn; Deploy a Machine Learning Web App with Heroku; How to Ace Data Science Assessment Test by Using Automatic EDA Tools; Will DeepMind’s AlphaCode Replace Programmers?

  https://www.kdnuggets.com/2022/n16.html

• Top YouTube Channels for Learning Data Science

  YouTube has become an important element in people's self-development and increase of knowledge. Check out this list of YouTube channels that offer Data Science learning.

  https://www.kdnuggets.com/2022/04/top-youtube-channels-learning-data-science.html

• Deploy a Machine Learning Web App with Heroku

  In this article, you will learn to deploy a fully functional ML web application in under 3 minutes.

  https://www.kdnuggets.com/2022/04/deploy-machine-learning-web-app-heroku.html

• With Data Privacy learn to implement technical privacy solutions and tools at scale

  Data Privacy: A runbook for engineers, teaches you to implement technical privacy solutions and tools at scale. Master methods that can be instantly applied to almost any system, and rapidly improve your user privacy saving time and resource costs!

  https://www.kdnuggets.com/2022/04/manning-data-privacy-learn-implement-technical-privacy-solutions-tools-scale.html

• 4 Factors to Identify Machine Learning Solvable Problems

  The near future holds incredible possibility for machine learning to solve real world problems. But we need to be be able to determine which problems are solvable by ML and which are not.

  https://www.kdnuggets.com/2022/04/4-factors-identify-machine-learning-solvable-problems.html

• KDnuggets News, April 6: 8 Free MIT Courses to Learn Data Science Online; The Complete Collection Of Data Repositories – Part 1

  8 Free MIT Courses to Learn Data Science Online; The Complete Collection Of Data Repositories - Part 1; DBSCAN Clustering Algorithm in Machine Learning; Introductory Pandas Tutorial; People Management for AI: Building High-Velocity AI Teams

  https://www.kdnuggets.com/2022/n14.html

• DBSCAN Clustering Algorithm in Machine Learning

  An introduction to the DBSCAN algorithm and its implementation in Python.

  https://www.kdnuggets.com/2020/04/dbscan-clustering-algorithm-machine-learning.html

• Machine Learning Pipeline Optimization with TPOT

  Let's revisit the automated machine learning project TPOT, and get back up to speed on using open source AutoML tools on our way to building a fully-automated prediction pipeline.

  https://www.kdnuggets.com/2021/05/machine-learning-pipeline-optimization-tpot.html

• 8 Free MIT Courses to Learn Data Science Online

  Create a data science learning path with courses from the world’s most prestigious university.

  https://www.kdnuggets.com/2022/03/8-free-mit-courses-learn-data-science-online.html

• Machine Learning Textbook: Stochastic Processes and Simulations

  The 100 page book on stochastic processes. Published in 2022. This off-the-beaten-path machine learning tutorial is designed for busy professionals, researchers and students eager to learn and apply methods ranging from simple to advanced, in a minimum amount of time. Offered with data sets, source code, videos, spreadsheets and solved exercises.

  https://www.kdnuggets.com/2022/03/datashaping-machine-learning-textbook-stochastic-processes-simulations.html

• A New Way of Managing Deep Learning Datasets

  Create, version-control, query, and visualize image, audio, and video datasets using Hub 2.0 by Activeloop.

  https://www.kdnuggets.com/2022/03/new-way-managing-deep-learning-datasets.html

• DIY Automated Machine Learning with Streamlit

  In this article, we will create an automated machine learning web app you can actually use.

  https://www.kdnuggets.com/2021/11/diy-automated-machine-learning-app.html

• Feature Stores for Real-time AI & Machine Learning

  Real-time AI/ML is on the rise and feature stores are key to successfully deploying them. Read on to see how the choice of online store and the feature store architecture play important roles in determining its performance and cost.

  https://www.kdnuggets.com/2022/03/feature-stores-realtime-ai-machine-learning.html

• KDnuggets News March 16, 2022: Learn Data Science Fundamentals & 5 Steps to Become a Data Scientist

  How Long Does It Take to Learn Data Science Fundamentals?; Become a Data Science Professional in Five Steps; New Ways of Sharing Code Blocks for Data Scientists; Machine Learning Algorithms for Classification; The Significance of Data Quality in Making a Successful Machine Learning Model

  https://www.kdnuggets.com/2022/n11.html

• Why Do Most People Fail to Learn Programming?

  Have you spent hours taking coding bootcamps, online courses, and tutorials, only to feel like you aren’t getting anywhere?

  https://www.kdnuggets.com/2022/03/people-fail-learn-programming.html

• Machine Learning Algorithms for Classification

  In this article, we will be going through the algorithms that can be used for classification tasks.

  https://www.kdnuggets.com/2022/03/machine-learning-algorithms-classification.html

• The Significance of Data Quality in Making a Successful Machine Learning Model

  Good quality data becomes imperative and a basic building block of an ML pipeline. The ML model can only be as good as its training data.

  https://www.kdnuggets.com/2022/03/significance-data-quality-making-successful-machine-learning-model.html

• How To Use Synthetic Data To Overcome Data Shortages For Machine Learning Model Training

  It takes time and considerable resources to collect, document, and clean data before it can be used. But there is a way to address this challenge – by using synthetic data.

  https://www.kdnuggets.com/2022/03/synthetic-data-overcome-data-shortages-machine-learning-model-training.html

• How Long Does It Take to Learn Data Science Fundamentals?

  This article discusses 2 levels of data science learning, and the amount of time that will need to go into each. From 6 months to 4 years, this write-up covers a number of skills and how long it takes to acquire them.

  https://www.kdnuggets.com/2022/03/long-take-learn-data-science-fundamentals.html

• KDnuggets News March 9, 2022: Build a Machine Learning Web App in 5 Minutes; 5 Applications of Computer Vision

  This week's top posts are: Build a Machine Learning Web App in 5 Minutes by Natassha Selvaraj; 5 Applications of Computer Vision by Devin Partida; 5 Data Science Projects to Learn 5 Critical Data Science Skills by Nate Rosidi

  https://www.kdnuggets.com/2022/n10.html

• 5 Data Science Projects to Learn 5 Critical Data Science Skills

  Learn these to take any data science project idea from brainstorm to deployment.

  https://www.kdnuggets.com/2022/03/5-data-science-projects-learn-5-critical-data-science-skills.html

• Build a Machine Learning Web App in 5 Minutes

  In this article, you will learn to export your models and use them outside a Jupyter Notebook environment. You will build a simple web application that is able to feed user input into a machine learning model, and display an output prediction to the user.

  https://www.kdnuggets.com/2022/03/build-machine-learning-web-app-5-minutes.html

• What is Adversarial Machine Learning?

  In the Cybersecurity sector Adversarial machine learning attempts to deceive and trick models by creating unique deceptive inputs, to confuse the model resulting in a malfunction in the model. 

  https://www.kdnuggets.com/2022/03/adversarial-machine-learning.html

• Top 3 Free Resources to Learn Linear Algebra for Machine Learning

  This article will solely focus on learning linear algebra, as it forms the backbone of machine learning model implementation.

  https://www.kdnuggets.com/2022/03/top-3-free-resources-learn-linear-algebra-machine-learning.html

• Calculus: The hidden building block of machine learning

  Unless you have a basic knowledge of calculus, you cannot understand how machine learning algorithms are developed. Calculus for Machine Learning is designed for developers to get you up to speed on the calculus that you need for applied machine learning. The book has more math than our other books and over 85 code examples to help you understand the concepts.

  https://www.kdnuggets.com/2022/02/mlm-hidden-building-block-machine-learning.html

• How to Create a Dataset for Machine Learning

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

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

• PyTorch or TensorFlow? Comparing popular Machine Learning frameworks

  Machine Learning with PyTorch and Scikit-learn is the PyTorch book from the widely acclaimed and bestselling Python Machine Learning series, fully updated and expanded to cover PyTorch, transformers, graph neural networks, and best practices.

  https://www.kdnuggets.com/2022/02/packt-pytorch-tensorflow-comparing-popular-machine-learning-frameworks.html

• Design Patterns in Machine Learning for MLOps

  This article outlines some of the most common design patterns encountered when creating successful Machine Learning solutions.

  https://www.kdnuggets.com/2022/02/design-patterns-machine-learning-mlops.html

• Essential Machine Learning Algorithms: A Beginner’s Guide

  Machine Learning as a technology, ensures that our current gadgets and their software get smarter by the day. Here are the algorithms that you ought to know about to understand Machine Learning’s varied and extensive functionalities and their effectiveness.

  https://www.kdnuggets.com/2021/05/essential-machine-learning-algorithms-beginners.html

• The Challenges of Creating Features for Machine Learning

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

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

• How You Can Use Machine Learning to Automatically Label Data

  AI and machine learning can provide us with these tools. This guide will explore how we can use machine learning to label data.

  https://www.kdnuggets.com/2022/02/machine-learning-automatically-label-data.html

• An Easy Guide to Choose the Right Machine Learning Algorithm

  There's no free lunch in machine learning. So, determining which algorithm to use depends on many factors from the type of problem at hand to the type of output you are looking for. This guide offers several considerations to review when exploring the right ML approach for your dataset.

  https://www.kdnuggets.com/2020/05/guide-choose-right-machine-learning-algorithm.html

• KDnuggets™ News 22:n07, Feb 16: How to Learn Math for Machine Learning; Data Mesh & Its Distributed Data Architecture

  How to Learn Math for Machine Learning; Data Mesh & Its Distributed Data Architecture; 5 Ways to Apply AI to Small Data Sets; Top 5 Free Machine Learning Courses; Junior Data Scientist: The Next Level

  https://www.kdnuggets.com/2022/n07.html

• Free MIT Courses on Calculus: The Key to Understanding Deep Learning

  Calculus is the key to fully understanding how neural networks function. Go beyond a surface understanding of this mathematics discipline with these free course materials from MIT.

  https://www.kdnuggets.com/2020/07/free-mit-courses-calculus-key-deep-learning.html

• Top 5 Free Machine Learning Courses

  Give a boost to your career and learn job-ready machine learning skills by taking the best free online courses.

  https://www.kdnuggets.com/2022/02/top-5-free-machine-learning-courses.html

• How to Learn Math for Machine Learning

  So how much math do you need to know in order to work in the data science industry? The answer: Not as much as you think.

  https://www.kdnuggets.com/2022/02/learn-math-machine-learning.html

• KDnuggets™ News 22:n05, Feb 2: 7 Steps to Mastering Machine Learning with Python in 2022; Unable to Land a Data Science Job? Here’s Why

  7 Steps to Mastering Machine Learning with Python in 2022; Unable to Land a Data Science Job? Here’s Why; R vs Python (Again): A Human Factor Perspective; How To Design Your Data Science Portfolio; Experience the best of both Windows and Ubuntu

  https://www.kdnuggets.com/2022/n05.html

• Effective Testing for Machine Learning

  Given how uncertain ML projects are, this is an incremental strategy that you can adopt as your project matures; it includes test examples to provide a clear idea of how these tests look in practice, and a complete project implementation is available on GitHub. By the end of the post, you’ll be able to develop more robust ML pipelines.

  https://www.kdnuggets.com/2022/01/effective-testing-machine-learning.html

• Deep Learning with Python: Second Edition by François Chollet

  Now in print! New edition of the bestselling original by François Chollet.

  https://www.kdnuggets.com/2022/01/manning-deep-learning-python-second-edition-francois-chollet.html

• TensorFlow for Computer Vision – Transfer Learning Made Easy

  In this article, see how you can get above 90% accuracy on the validation set with a pretty straightforward approach. You'll also see what happens to the validation accuracy if we scale down the amount of training data by a factor of 20. Spoiler alert - it will remain unchanged.

  https://www.kdnuggets.com/2022/01/tensorflow-computer-vision-transfer-learning-made-easy.html

• Learn Machine Learning 4X Faster by Participating in Competitions

  Participating in competitions has taught me everything about machine learning and how It can help you learn multiple domains faster than online courses.

  https://www.kdnuggets.com/2022/01/learn-machine-learning-4x-faster-participating-competitions.html

• The Best Learning Resources for Data Science in 2022

  Unclutter your space and learn about the best books, free tutorials, courses, platforms, and certifications to start your data science journey.

  https://www.kdnuggets.com/2022/01/best-learning-resources-data-science-2022.html

• Models Are Rarely Deployed: An Industry-wide Failure in Machine Learning Leadership

  In this article, Eric Siegel summarizes the recent KDnuggets poll results and argues that the pervasive failure of ML projects comes from a lack of prudent leadership. He also argues that MLops is not the fundamental missing ingredient – instead, an effective ML leadership practice must be the dog that wags the model-integration tail.

  https://www.kdnuggets.com/2022/01/models-rarely-deployed-industrywide-failure-machine-learning-leadership.html

• Transfer Learning for Image Recognition and Natural Language Processing

  Read the second article in this series on Transfer Learning, and learn how to apply it to Image Recognition and Natural Language Processing.

  https://www.kdnuggets.com/2022/01/transfer-learning-image-recognition-natural-language-processing.html

• A (Much) Better Approach to Evaluate Your Machine Learning Model

  Using one or two performance metrics seems sufficient to claim that your ML model is good — chances are that it’s not.

  https://www.kdnuggets.com/2022/01/much-better-approach-evaluate-machine-learning-model.html

• A Full End-to-End Deployment of a Machine Learning Algorithm into a Live Production Environment

  How to use scikit-learn, pickle, Flask, Microsoft Azure and ipywidgets to fully deploy a Python machine learning algorithm into a live, production environment.

  https://www.kdnuggets.com/2021/12/deployment-machine-learning-algorithm-live-production-environment.html

• What is Transfer Learning?

  During transfer learning, the knowledge leveraged and rapid progress from a source task is used to improve the learning and development to a new target task. Read on for a deeper dive on the subject.

  https://www.kdnuggets.com/2022/01/transfer-learning.html

• Why Do Machine Learning Models Die In Silence?

  A critical problem for companies when integrating machine learning in their business processes is not knowing why they don't perform well after a while. The reason is called concept drift. Here's an informational guide to understanding the concept well.

  https://www.kdnuggets.com/2022/01/machine-learning-models-die-silence.html

• Why are More Developers Using Python for Their Machine Learning Projects?

  To support the creation of new and exciting ML and artificial intelligence (AI) applications, developers need a robust programming language. That's where the Python programming language comes in.

  https://www.kdnuggets.com/2022/01/developers-python-machine-learning-projects.html

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

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

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

• Hands-on Reinforcement Learning Course Part 3: SARSA

  This is part 3 of my hands-on course on reinforcement learning, which takes you from zero to HERO . Today we will learn about SARSA, a powerful RL algorithm.

  https://www.kdnuggets.com/2022/01/handson-reinforcement-learning-course-part-3-sarsa.html

• 4 Reasons Why You Shouldn’t Use Machine Learning

  It's time to learn: machine learning is not a Swiss Army knife.

  https://www.kdnuggets.com/2021/12/4-reasons-shouldnt-machine-learning.html

• Hands-On Reinforcement Learning Course, Part 2

  Continue your learning journey in Reinforcement Learning with this second of two part tutorial that covers the foundations of the technique with examples and Python code.

  https://www.kdnuggets.com/2021/12/hands-on-reinforcement-learning-part-2.html

• Versioning Machine Learning Experiments vs Tracking Them

  Learn how to improve ML reproducibility by treating experiments as code.

  https://www.kdnuggets.com/2021/12/versioning-machine-learning-experiments-tracking.html

• Tips & Tricks of Deploying Deep Learning Webapp on Heroku Cloud

  Learn model deployment issues and solutions on deploying a TensorFlow-based image classifier Streamlit app on a Heroku server.

  https://www.kdnuggets.com/2021/12/tips-tricks-deploying-dl-webapps-heroku.html

• Alternative Feature Selection Methods in Machine Learning

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

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

• Hands-On Reinforcement Learning Course, Part 1

  Start your learning journey in Reinforcement Learning with this first of two part tutorial that covers the foundations of the technique with examples and Python code.

  https://www.kdnuggets.com/2021/12/hands-on-reinforcement-learning-course-part-1.html

• Machine learning does not produce value for my business. Why?

  What is going on when machine learning can't make the jump from testing to production, and so doesn't add any business value?

  https://www.kdnuggets.com/2021/12/machine-learning-produce-value-business.html

• Federated Learning: Collaborative Machine Learning with a Tutorial on How to Get Started

  Read on to learn more about the intricacies of federated learning and what it can do for machine learning on sensitive data.

  https://www.kdnuggets.com/2021/12/federated-learning-collaborative-machine-learning-tutorial-get-started.html

• Top Resources for Learning Statistics for Data Science">Top Resources for Learning Statistics for Data Science

  Let’s take a look at the current state of statistics in data science, and what you can do to accelerate your learning.

  https://www.kdnuggets.com/2021/12/springboard-top-resources-learn-data-science-statistics.html

• KDnuggets™ News 21:n47, Dec 15: Building a solid data team; Stop Learning Data Science to Find Purpose and Find Purpose to Learn Data Science; AI, Analytics, Machine Learning, Data Science Main Developments in 2021 and Key Trends for 2022

  In this issue: Building a solid data team; Stop Learning Data Science to Find Purpose and Find Purpose to Learn Data Science; AI, Analytics, Machine Learning, Data Science, Deep Learning Main Developments in 2021 and Key Trends for 2022 - Research, Technology, and Industry perspectives.

  https://www.kdnuggets.com/2021/n47.html

• Data Labeling for Machine Learning: Market Overview, Approaches, and Tools

  So much of data science and machine learning is founded on having clean and well-understood data sources that it is unsurprising that the data labeling market is growing faster than ever. Here, we highlight many of the top players in this industry and the techniques they use to help you consider which might make a good partner for your needs.

  https://www.kdnuggets.com/2021/12/data-labeling-ml-overview-and-tools.html

• Stop Learning Data Science to Find Purpose and Find Purpose to Learn Data Science">Stop Learning Data Science to Find Purpose and Find Purpose to Learn Data Science

  How I flipped the educational model to become a more effective data scientist.

  https://www.kdnuggets.com/2021/12/stop-learning-data-science-find-purpose.html

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

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

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

• Inside DeepMind’s New Efforts to Use Deep Learning to Advance Mathematics

  Using deep learning techniques can help mathematicians develop intuitions about the toughest problems in the field.

  https://www.kdnuggets.com/2021/12/inside-deepmind-new-efforts-deep-learning-advance-mathematics.html

• AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2021 and Key Trends for 2022

  2021 has almost come and gone. We saw some standout advancements in AI, Analytics, Machine Learning, Data Science, Deep Learning Research this past year, and the future, starting with 2022, looks bright. As per KDnuggets tradition, our collection of experts have contributed their insights on the matter. Read on to find out more.

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

• Using Datawig, an AWS Deep Learning Library for Missing Value Imputation

  A lot of missing values in the dataset can affect the quality of prediction in the long run. Several methods can be used to fill the missing values and Datawig is one of the most efficient ones.

  https://www.kdnuggets.com/2021/12/datawig-aws-deep-learning-library-missing-value-imputation.html

• A Beginner’s Guide to End to End Machine Learning

  Learn to train, tune, deploy and monitor machine learning models.

  https://www.kdnuggets.com/2021/12/beginner-guide-end-end-machine-learning.html

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

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

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

• Building Massively Scalable Machine Learning Pipelines with Microsoft Synapse ML

  The new platform provides a single API to abstract dozens of ML frameworks and databases.

  https://www.kdnuggets.com/2021/11/building-massively-scalable-machine-learning-pipelines-microsoft-synapse-ml.html

• New Poll: What Percentage of Your Machine Learning Models Have Been Deployed?

  Take a moment to participate in the latest KDnuggets poll and let the community know what percentage of your machine learning models have been deployed.

  https://www.kdnuggets.com/2021/11/percentage-machine-learning-models-deployed.html

• Why Machine Learning Engineers are Replacing Data Scientists">Why Machine Learning Engineers are Replacing Data Scientists

  The hiring run for data scientists continues along at a strong clip around the world. But, there are other emerging roles that are demonstrating key value to organizations that you should consider based on your existing or desired skill sets.

  https://www.kdnuggets.com/2021/11/why-machine-learning-engineers-are-replacing-data-scientists.html

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

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

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

• 3 Differences Between Coding in Data Science and Machine Learning

  The terms ‘data science’ and ‘machine learning’ are often used interchangeably. But while they are related, there are some glaring differences, so let’s take a look at the differences between the two disciplines, specifically as it relates to programming.

  https://www.kdnuggets.com/2021/11/3-differences-coding-data-science-machine-learning.html

• Difference between distributed learning versus federated learning algorithms

  Want to know the difference between distributed and federated learning? Read this article to find out.

  https://www.kdnuggets.com/2021/11/difference-distributed-learning-federated-learning-algorithms.html

• Anecdotes from 11 Role Models in Machine Learning

  The skills needed to create good data are also the skills needed for good leadership.

  https://www.kdnuggets.com/2021/11/anecdotes-11-role-models-machine-learning.html

• Deep Learning on your phone: PyTorch C++ API for use on Mobile Platforms

  The PyTorch Deep Learning framework has a C++ API for use on mobile platforms. This article shows an end-to-end demo of how to write a simple C++ application with Deep Learning capabilities using the PyTorch C++ API such that the same code can be built for use on mobile platforms (both Android and iOS).

  https://www.kdnuggets.com/2021/11/deep-learning-mobile-phone-pytorch-c-api.html

• The Common Misconceptions About Machine Learning

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

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

• What Comes After HDF5? Seeking a Data Storage Format for Deep Learning

  In this article we are discussing that HDF5 is one of the most popular and reliable formats for non-tabular, numerical data. But this format is not optimized for deep learning work. This article suggests what kind of ML native data format should be to truly serve the needs of modern data scientists.

  https://www.kdnuggets.com/2021/11/after-hdf5-data-storage-format-deep-learning.html

• Federated Learning: Google’s Take

  This blog will be focusing on the work Google has been doing in the Federated Learning space.

  https://www.kdnuggets.com/2021/11/federated-learning-googles-take.html

• Toloka 101 Live Demo: Learn how to get reliable training data for machine learning, Nov 11

  Toloka is a crowdsourced data labeling platform that handles data collection and annotation projects for machine learning at any scale. In this Nov 11 Live Demo, Learn how to get reliable training data for machine learning.

  https://www.kdnuggets.com/2021/11/toloka-training-data-machine-learning.html

• 7 of The Coolest Machine Learning Topics of 2021 at ODSC West

  At our upcoming event this November 16th-18th in San Francisco, ODSC West 2021 will feature a plethora of talks, workshops, and training sessions on machine learning topics, deep learning, NLP, MLOps, and so on. You can register now for 20% off all ticket types, or register for a free AI Expo Pass to see what some big names in AI are doing now.

  https://www.kdnuggets.com/2021/11/odsc-7-coolest-machine-learning-topics.html

• Design Patterns for Machine Learning Pipelines">Design Patterns for Machine Learning Pipelines

  ML pipeline design has undergone several evolutions in the past decade with advances in memory and processor performance, storage systems, and the increasing scale of data sets. We describe how these design patterns changed, what processes they went through, and their future direction.

  https://www.kdnuggets.com/2021/11/design-patterns-machine-learning-pipelines.html

• Machine Learning Model Development and Model Operations: Principles and Practices">Machine Learning Model Development and Model Operations: Principles and Practices

  The ML model management and the delivery of highly performing model is as important as the initial build of the model by choosing right dataset. The concepts around model retraining, model versioning, model deployment and model monitoring are the basis for machine learning operations (MLOps) that helps the data science teams deliver highly performing models.

  https://www.kdnuggets.com/2021/10/machine-learning-model-development-operations-principles-practice.html

• How To Defeat The Machine Learning Engineer Impostor Syndrome

  How many times have you taken yet another online course on machine learning or read yet another paper on a new emerging topic, to be up-to-date in this crazy fast-paced AI/ML world -- only to keep feeling like an ML engineer impostor? These three personal tips can help you overcome the classic (and common) impostor syndrome behind every emerging ML engineer who wants to be better at what you do.

  https://www.kdnuggets.com/2021/10/defeat-machine-learning-engineer-impostor-syndrome.html

• Guide To Finding The Right Predictive Maintenance Machine Learning Techniques

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

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

• Learn To Reproduce Papers: Beginner’s Guide">Learn To Reproduce Papers: Beginner’s Guide

  Step-by-step instructions on how to understand Deep Learning papers and implement the described approaches.

  https://www.kdnuggets.com/2021/10/learn-reproduce-papers-beginners-guide.html

• KDnuggets™ News 21:n40, Oct 20: The 20 Python Packages You Need For Machine Learning and Data Science; Ace Data Science Interviews with Portfolio Projects

  The 20 Python Packages You Need For Machine Learning and Data Science; How to Ace Data Science Interview by Working on Portfolio Projects; Deploying Your First Machine Learning API; Real Time Image Segmentation Using 5 Lines of Code; What is Clustering and How Does it Work?

  https://www.kdnuggets.com/2021/n40.html

• How to calculate confidence intervals for performance metrics in Machine Learning using an automatic bootstrap method

  Are your model performance measurements very precise due to a “large” test set, or very uncertain due to a “small” or imbalanced test set?

  https://www.kdnuggets.com/2021/10/calculate-confidence-intervals-performance-metrics-machine-learning.html

• Deploying Your First Machine Learning API">Deploying Your First Machine Learning API

  Effortless way to develop and deploy your machine learning API using FastAPI and Deta.

  https://www.kdnuggets.com/2021/10/deploying-first-machine-learning-api.html

• The 20 Python Packages You Need For Machine Learning and Data Science">The 20 Python Packages You Need For Machine Learning and Data Science

  Do you do Python? Do you do data science and machine learning? Then, you need to do these crucial Python libraries that enable nearly all you will want to do.

  https://www.kdnuggets.com/2021/10/20-python-packages.html

• AutoML: An Introduction Using Auto-Sklearn and Auto-PyTorch

  AutoML is a broad category of techniques and tools for applying automated search to your automated search and learning to your learning. In addition to Auto-Sklearn, the Freiburg-Hannover AutoML group has also developed an Auto-PyTorch library. We’ll use both of these as our entry point into AutoML in the following simple tutorial.

  https://www.kdnuggets.com/2021/10/automl-introduction-auto-sklearn-auto-pytorch.html

• Building and Operationalizing Machine Learning Models: Three tips for success

  With more enterprises implementing machine learning to improve revenue and operations, properly operationalizing the ML lifecycle in a holistic way is crucial for data teams to make their projects efficient and effective.

  https://www.kdnuggets.com/2021/10/building-operationalizing-machine-learning-models.html

• Here’s Why You Need Python Skills as a Machine Learning Engineer">Here’s Why You Need Python Skills as a Machine Learning Engineer

  If you want to learn how to apply Python programming skills in the context of AI applications, the UC San Diego Extension Machine Learning Engineering Bootcamp can help. Read on to find out more about how machine learning engineers use Python, and why the language dominates today’s machine learning landscape.

  https://www.kdnuggets.com/2021/10/bootcamp-python-skills-machine-learning-engineer.html

• A Breakdown of Deep Learning Frameworks

  Deep Learning continues to evolve as one of the most powerful techniques in the AI toolbox. Many software packages exist today to support the development of models, and we highlight important options available with key qualities and differentiators to help you select the most appropriate for your needs.

  https://www.kdnuggets.com/2021/09/a-breakdown-deep-learning-frameworks.html

• 9 Outstanding Reasons to Learn Python for Finance

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

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

• 20 Machine Learning Projects That Will Get You Hired">20 Machine Learning Projects That Will Get You Hired

  If you want to break into the machine learning and data science job market, then you will need to demonstrate the proficiency of your skills, especially if you are self-taught through online courses and bootcamps. A project portfolio is a great way to practice your new craft and offer convincing evidence that an employee should hire you over the competition.

  https://www.kdnuggets.com/2021/09/20-machine-learning-projects-hired.html

• Nine Tools I Wish I Mastered Before My PhD in Machine Learning">Nine Tools I Wish I Mastered Before My PhD in Machine Learning

  Whether you are building a start up or making scientific breakthroughs these tools will bring your ML pipeline to the next level.

  https://www.kdnuggets.com/2021/09/nine-tools-mastered-before-phd-machine-learning.html

• KDnuggets™ News 21:n36, Sep 22: The Machine & Deep Learning Compendium Open Book; Easy SQL in Native Python

  The Machine & Deep Learning Compendium Open Book; Easy SQL in Native Python; Introduction to Automated Machine Learning; How to be a Data Scientist without a STEM degree; What Is The Real Difference Between Data Engineers and Data Scientists?

  https://www.kdnuggets.com/2021/n36.html

• How to Find Weaknesses in your Machine Learning Models">How to Find Weaknesses in your Machine Learning Models

  FreaAI: a new method from researchers at IBM.

  https://www.kdnuggets.com/2021/09/weaknesses-machine-learning-models.html

• The Machine & Deep Learning Compendium Open Book">The Machine & Deep Learning Compendium Open Book

  After years in the making, this extensive and comprehensive ebook resource is now available and open for data scientists and ML engineers. Learn from and contribute to this tome of valuable information to support all your work in data science from engineering to strategy to management.

  https://www.kdnuggets.com/2021/09/machine-deep-learning-open-book.html

• Introduction to Automated Machine Learning

  AutoML enables developers with limited ML expertise (and coding experience) to train high-quality models specific to their business needs. For this article, we will focus on AutoML systems which cater to everyday business and technology applications.

  https://www.kdnuggets.com/2021/09/introduction-automated-machine-learning.html

• An Introduction to Reinforcement Learning with OpenAI Gym, RLlib, and Google Colab

  Get an Introduction to Reinforcement Learning by attempting to balance a virtual CartPole with OpenAI Gym, RLlib, and Google Colab.

  https://www.kdnuggets.com/2021/09/intro-reinforcement-learning-openai-gym-rllib-colab.html

• 3 Most Important Lessons I’ve Learned 3 Years Into My Data Science Career

  After only 3 years of working as a data professional, many tried-and-true lessons can be learned. Here are 3 of the most important lessons learned with key takeaways and reflections shared.

  https://www.kdnuggets.com/2021/09/3-important-lessons-data-science-career.html

• Text Preprocessing Methods for Deep Learning

  While the preprocessing pipeline we are focusing on in this post is mainly centered around Deep Learning, most of it will also be applicable to conventional machine learning models too.

  https://www.kdnuggets.com/2021/09/text-preprocessing-methods-deep-learning.html

• 8 Deep Learning Project Ideas for Beginners">8 Deep Learning Project Ideas for Beginners

  Have you studied Deep Learning techniques, but never worked on a useful project? Here, we highlight eight deep learning project ideas for beginners that will help you sharpen your skills and boost your resume.

  https://www.kdnuggets.com/2021/09/8-deep-learning-project-ideas-beginners.html

• Top 18 Low-Code and No-Code Machine Learning Platforms">Top 18 Low-Code and No-Code Machine Learning Platforms

  Machine learning becomes more accessible to companies and individuals when there is less coding involved. Especially if you are just starting your path in ML, then check out these low-code and no-code platforms to help expedite your capabilities in learning and applying AI.

  https://www.kdnuggets.com/2021/09/top-18-low-code-no-code-machine-learning-platforms.html