Search results for Programming Probability

Found 242 documents, 5946 searched:

• How to Prepare Your Data

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

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

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

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

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

• I Designed My Own Machine Learning and AI Degree

  With so many pioneering online resources for open education, check out this organized collection of courses you can follow to become a well-rounded machine learning and AI engineer.

  https://www.kdnuggets.com/2020/05/designed-machine-learning-ai-degree.html

• What You Need to Know About Deep Reinforcement Learning

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

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

• Start Your Machine Learning Career in Quarantine">Start Your Machine Learning Career in Quarantine

  While this quarantine can last two months, make the most of it by starting your career in Machine Learning with this 60-day learning plan.

  https://www.kdnuggets.com/2020/05/machine-learning-career-quarantine.html

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

  https://www.kdnuggets.com/2020/03/time-series-classification-synthetic-real-financial-time-series.html

• Decision Boundary for a Series of Machine Learning Models

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

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

• Math for Programmers!

  Math for Programmers teaches you the math you need to know for a career in programming, concentrating on what you need to know as a developer.

  https://www.kdnuggets.com/2020/03/manning-math-programmers.html

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

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

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

• Decision Tree Intuition: From Concept to Application

  While the use of Decision Trees in machine learning has been around for awhile, the technique remains powerful and popular. This guide first provides an introductory understanding of the method and then shows you how to construct a decision tree, calculate important analysis parameters, and plot the resulting tree.

  https://www.kdnuggets.com/2020/02/decision-tree-intuition.html

• Data Science Curriculum for self-study

  Are you asking the question, "how do I become a Data Scientist?" This list recommends the best essential topics to gain an introductory understanding for getting started in the field. After learning these basics, keep in mind that doing real data science projects through internships or competitions is crucial to acquiring the core skills necessary for the job.

  https://www.kdnuggets.com/2020/02/data-science-curriculum-self-study.html

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

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

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

• 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 1)">20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 1)

  2020 is well underway, and we bring you 20 AI, data science, and machine learning terms we should all be familiar with as the year marches onward.

  https://www.kdnuggets.com/2020/02/ai-data-science-machine-learning-key-terms-2020.html

• Math for Programmers – your guide for solving math problems in code">Math for Programmers – your guide for solving math problems in code

  Math for Programmers teaches you the math you need to know for a career in programming, concentrating on what you need to know as a developer.

  https://www.kdnuggets.com/2020/02/manning-math-programmers.html

• Optimal Estimation Algorithms: Kalman and Particle Filters

  An introduction to the Kalman and Particle Filters and their applications in fields such as Robotics and Reinforcement Learning.

  https://www.kdnuggets.com/2020/02/optimal-estimation-algorithms-kalman-particle-filters.html

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

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

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

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

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

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

• The Data Science Interview Study Guide

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

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

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

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

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

• Top 9 Mobile Apps for Learning and Practicing Data Science">Top 9 Mobile Apps for Learning and Practicing Data Science

  This article will tell you about the top 9 mobile apps that help the user in learning and practicing data science and hence is improving their productivity.

  https://www.kdnuggets.com/2020/01/top-9-mobile-apps-learning-practicing-data-science.html

• Math for Programmers!">Math for Programmers!

  Math for Programmers teaches you the math you need to know for a career in programming, concentrating on what you need to know as a developer.

  https://www.kdnuggets.com/2020/01/manning-math-programmers.html

• An Introductory Guide to NLP for Data Scientists with 7 Common Techniques">An Introductory Guide to NLP for Data Scientists with 7 Common Techniques

  Data Scientists work with tons of data, and many times that data includes natural language text. This guide reviews 7 common techniques with code examples to introduce you the essentials of NLP, so you can begin performing analysis and building models from textual data.

  https://www.kdnuggets.com/2020/01/intro-guide-nlp-data-scientists.html

• A Comprehensive Guide to Natural Language Generation

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

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

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

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

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

• 10 Best and Free Machine Learning Courses, Online

  Getting ready to leap into the world of Data Science? Consider these top machine learning courses curated by experts to help you learn and thrive in this exciting field.

  https://www.kdnuggets.com/2019/12/best-free-machine-learning-courses-online.html

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

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

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

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

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

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

• How To “Ultralearn” Data Science, Part 1

  What is "ultralearning" and how can you follow the strategy to become an expert of data science? Start with this first part in a series that will guide you through this self-motivated methodology to help you efficiently master difficult skills.

  https://www.kdnuggets.com/2019/12/ultralearn-data-science-part1.html

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

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

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

• Enabling the Deep Learning Revolution

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

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

• Data Science Curriculum Roadmap">Data Science Curriculum Roadmap

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

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

• Markov Chains: How to Train Text Generation to Write Like George R. R. Martin

  Read this article on training Markov chains to generate George R. R. Martin style text.

  https://www.kdnuggets.com/2019/11/markov-chains-train-text-generation.html

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

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

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

• Build an Artificial Neural Network From Scratch: Part 1

  This article focused on building an Artificial Neural Network using the Numpy Python library.

  https://www.kdnuggets.com/2019/11/build-artificial-neural-network-scratch-part-1.html

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

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

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

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

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

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

• How to count Big Data: Probabilistic data structures and algorithms

  Learn how probabilistic data structures and algorithms can be used for cardinality estimation in Big Data streams.

  https://www.kdnuggets.com/2019/08/count-big-data-probabilistic-data-structures-algorithms.html

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

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

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

• Introduction to Image Segmentation with K-Means clustering

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

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

• Things I Have Learned About Data Science

  Read this collection of 38 things the author has learned along his travels, and has opted to share for the benefit of the reader.

  https://www.kdnuggets.com/2019/07/collection-things-learned-data-science.html

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

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

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

• What’s wrong with the approach to Data Science?">What’s wrong with the approach to Data Science?

  The job ‘Data Scientist’ has been around for decades, it was just not called “Data Scientist”. Statisticians have used their knowledge and skills using machine learning techniques such as Logistic Regression and Random Forest for prediction and insights for longer than people actually realize.

  https://www.kdnuggets.com/2019/07/whats-wrong-with-data-science.html

• Optimization with Python: How to make the most amount of money with the least amount of risk?

  Learn how to apply Python data science libraries to develop a simple optimization problem based on a Nobel-prize winning economic theory for maximizing investment profits while minimizing risk.

  https://www.kdnuggets.com/2019/06/optimization-python-money-risk.html

• How to Learn Python for Data Science the Right Way">How to Learn Python for Data Science the Right Way

  The biggest mistake you can make while learning Python for data science is to learn Python programming from courses meant for programmers. Avoid this mistake, and learn Python the right way by following this approach.

  https://www.kdnuggets.com/2019/06/python-data-science-right-way.html

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

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

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

• Your Guide to Natural Language Processing (NLP)

  This extensive post covers NLP use cases, basic examples, Tokenization, Stop Words Removal, Stemming, Lemmatization, Topic Modeling, the future of NLP, and more.

  https://www.kdnuggets.com/2019/05/guide-natural-language-processing-nlp.html

• Customer Churn Prediction Using Machine Learning: Main Approaches and Models

  We reach out to experts from HubSpot and ScienceSoft to discuss how SaaS companies handle the problem of customer churn prediction using Machine Learning.

  https://www.kdnuggets.com/2019/05/churn-prediction-machine-learning.html

• 2019 Best Masters in Data Science and Analytics – Europe Edition">2019 Best Masters in Data Science and Analytics – Europe Edition

  We provide an updated list of our comprehensive, unbiased survey of graduate programs in Data Science and Analytics from across Europe.

  https://www.kdnuggets.com/2019/04/best-masters-data-science-analytics-europe.html

• Building NLP Classifiers Cheaply With Transfer Learning and Weak Supervision

  In this blog, I’ll walk you through a personal project in which I cheaply built a classifier to detect anti-semitic tweets, with no public dataset available, by combining weak supervision and transfer learning.

  https://www.kdnuggets.com/2019/03/building-nlp-classifiers-cheaply-transfer-learning-weak-supervision.html

• 2018’s Top 7 R Packages for Data Science and AI

  This is a list of the best packages that changed our lives this year, compiled from my weekly digests.

  https://www.kdnuggets.com/2019/01/vazquez-2018-top-7-r-packages.html

• Top Active Blogs on AI, Analytics, Big Data, Data Science, Machine Learning – updated

  Stay up-to-date with the latest technological advancements using our extensive list of active blogs; this is a list of 100 recently active blogs on Big Data, Data Science, Data Mining, Machine Learning, and Artificial intelligence.

  https://www.kdnuggets.com/2019/01/active-blogs-ai-analytics-data-science.html

• 10 More Must-See Free Courses for Machine Learning and Data Science">10 More Must-See Free Courses for Machine Learning and Data Science

  Have a look at this follow-up collection of free machine learning and data science courses to give you some winter study ideas.

  https://www.kdnuggets.com/2018/12/10-more-free-must-see-courses-machine-learning-data-science.html

• Solve any Image Classification Problem Quickly and Easily

  This article teaches you how to use transfer learning to solve image classification problems. A practical example using Keras and its pre-trained models is given for demonstration purposes.

  https://www.kdnuggets.com/2018/12/solve-image-classification-problem-quickly-easily.html

• Should you become a data scientist?">Should you become a data scientist?

  An overview of the current situation for data scientists, from its origins and history, to the recent growth in job postings, and looking at what changes the future might bring.

  https://www.kdnuggets.com/2018/12/should-i-become-a-data-scientist.html

• A comprehensive list of Machine Learning Resources: Open Courses, Textbooks, Tutorials, Cheat Sheets and more

  A thorough collection of useful resources covering statistics, classic machine learning, deep learning, probability, reinforcement learning, and more.

  https://www.kdnuggets.com/2018/12/finlayson-machine-learning-resources.html

• Kick Start Your Data Career! Tips From the Frontline

  I am going to provide very interesting and useful tips through this blog series which will help students to kick start their career in Data.

  https://www.kdnuggets.com/2018/12/kick-start-your-data-career.html

• Intro to Data Science for Managers">Intro to Data Science for Managers

  This mindmap contains a condensed introduction to the key data science concepts and techniques that have revolutionized the business landscape and became essential for making beneficial data-driven decisions

  https://www.kdnuggets.com/2018/11/intro-data-science-managers.html

• Introduction to Deep Learning with Keras

  In this article, we’ll build a simple neural network using Keras. Now let’s proceed to solve a real business problem: an insurance company wants you to develop a model to help them predict which claims look fraudulent.

  https://www.kdnuggets.com/2018/10/introduction-deep-learning-keras.html

• Naive Bayes from Scratch using Python only – No Fancy Frameworks

  We provide a complete step by step pythonic implementation of naive bayes, and by keeping in mind the mathematical & probabilistic difficulties we usually face when trying to dive deep in to the algorithmic insights of ML algorithms, this post should be ideal for beginners.

  https://www.kdnuggets.com/2018/10/naive-bayes-from-scratch-python.html

• 10 Best Mobile Apps for Data Scientist / Data Analysts">10 Best Mobile Apps for Data Scientist / Data Analysts

  A collection of useful mobile applications that will help enhance your vital data science and analytic skills. These free apps can improve your listening abilities, logical skills, basic leadership qualities and more.

  https://www.kdnuggets.com/2018/10/10-best-mobile-apps-data-scientist.html

• 7 Simple Data Visualizations You Should Know in R">7 Simple Data Visualizations You Should Know in R

  This post presents a selection of 7 essential data visualizations, and how to recreate them using a mix of base R functions and a few common packages.

  https://www.kdnuggets.com/2018/06/7-simple-data-visualizations-should-know-r.html

• Data Science Predicting The Future

  In this article we will expand on the knowledge learnt from the last article - The What, Where and How of Data for Data Science - and consider how data science is applied to predict the future.

  https://www.kdnuggets.com/2018/06/data-science-predicting-future.html

• Using Linear Regression for Predictive Modeling in R

  In this post, we’ll use linear regression to build a model that predicts cherry tree volume from metrics that are much easier for folks who study trees to measure.

  https://www.kdnuggets.com/2018/06/linear-regression-predictive-modeling-r.html

• 10 More Free Must-Read Books for Machine Learning and Data Science">10 More Free Must-Read Books for Machine Learning and Data Science

  Summer, summer, summertime. Time to sit back and unwind. Or get your hands on some free machine learning and data science books and get your learn on. Check out this selection to get you started.

  https://www.kdnuggets.com/2018/05/10-more-free-must-read-books-for-machine-learning-and-data-science.html

• 7 Books to Grasp Mathematical Foundations of Data Science and Machine Learning">7 Books to Grasp Mathematical Foundations of Data Science and Machine Learning

  It is vital to have a good understanding of the mathematical foundations to be proficient with data science. With that in mind, here are seven books that can help.

  https://www.kdnuggets.com/2018/04/7-books-mathematical-foundations-data-science.html

• How to Survive Your Data Science Interview

  There are many wonderful things about data science. It’s extreme breadth is not one of them. The title of data scientist means something different at every company

  https://www.kdnuggets.com/2018/03/survive-data-science-interview.html

• A Guide to Hiring Data Scientists

  This article provides a short overview of emerging data scientist types and their unique skillsets, as well as a guide for HR professionals and analytics managers who are looking to hire their first data scientists or build a data science team. Included are an overview of skills for each type and specific questions that can be asked to assess candidates.

  https://www.kdnuggets.com/2018/02/guide-hiring-data-scientists.html

• Top 15 Scala Libraries for Data Science in 2018

  For your convenience, we have prepared a comprehensive overview of the most important libraries used to perform machine learning and Data Science tasks in Scala.

  https://www.kdnuggets.com/2018/02/top-15-scala-libraries-data-science-2018.html

• The 8 Neural Network Architectures Machine Learning Researchers Need to Learn">The 8 Neural Network Architectures Machine Learning Researchers Need to Learn

  In this blog post, I want to share the 8 neural network architectures from the course that I believe any machine learning researchers should be familiar with to advance their work.

  https://www.kdnuggets.com/2018/02/8-neural-network-architectures-machine-learning-researchers-need-learn.html

• The Art of Learning Data Science">The Art of Learning Data Science

  A beginner’s account of getting into comfort zone of learning Data Science.

  https://www.kdnuggets.com/2018/01/art-learning-data-science.html

• How Much Mathematics Does an IT Engineer Need to Learn to Get Into Data Science?">How Much Mathematics Does an IT Engineer Need to Learn to Get Into Data Science?

  When I started diving deep into these exciting subjects (by self-study), I discovered quickly that I don’t know/only have a rudimentary idea about/ forgot mostly what I studied in my undergraduate study some essential mathematics.

  https://www.kdnuggets.com/2017/12/mathematics-needed-learn-data-science-machine-learning.html

• Best Masters in Data Science and Analytics – Europe Edition

  The third part of our comprehensive, unbiased survey of graduate programs in Data Science and Analytics, examining the programs from Europe.

  https://www.kdnuggets.com/2017/12/best-masters-data-science-analytics-europe.html

• The 10 Statistical Techniques Data Scientists Need to Master">The 10 Statistical Techniques Data Scientists Need to Master

  The author presents 10 statistical techniques which a data scientist needs to master. Build up your toolbox of data science tools by having a look at this great overview post.

  https://www.kdnuggets.com/2017/11/10-statistical-techniques-data-scientists-need-master.html

• Process Mining with R: Introduction

  In the past years, several niche tools have appeared to mine organizational business processes. In this article, we’ll show you that it is possible to get started with “process mining” using well-known data science programming languages as well.

  https://www.kdnuggets.com/2017/11/process-mining-r-introduction.html

• Getting Started with Machine Learning in One Hour!

  Here is a machine learning getting started guide which grew out of the author's notes for a one hour talk on the subject. Hopefully you find the path helpful.

  https://www.kdnuggets.com/2017/11/getting-started-machine-learning-one-hour.html

• Big Data Architecture: A Complete and Detailed Overview

  Data scientists may not be as educated or experienced in computer science, programming concepts, devops, site reliability engineering, non-functional requirements, software solution infrastructure, or general software architecture as compared to well-trained or experienced software architects and engineers.

  https://www.kdnuggets.com/2017/09/big-data-architecture-overview.html

• Machine Learning Exercises in Python: An Introductory Tutorial Series">Machine Learning Exercises in Python: An Introductory Tutorial Series

  This post presents a summary of a series of tutorials covering the exercises from Andrew Ng's machine learning class on Coursera. Instead of implementing the exercises in Octave, the author has opted to do so in Python, and provide commentary along the way.

  https://www.kdnuggets.com/2017/07/machine-learning-exercises-python-introductory-tutorial-series.html

• The Data Science of Steel, or Data Factory to Help Steel Factory

  Applying Machine Learning to steel production is really hard! Here are some lessons from Yandex researchers on how to balance the need for findings to be accurate, useful, and understandable at the same time.

  https://www.kdnuggets.com/2017/04/yandex-data-science-steel.html

• What Makes a Good Analyst?

  Without doubt, critical thinking is necessary in order to be a good analyst but particular skills and experience are also required. What are some of these skills?

  https://www.kdnuggets.com/2017/04/gray-makes-good-analyst.html

• 10 Free Must-Read Books for Machine Learning and Data Science">10 Free Must-Read Books for Machine Learning and Data Science

  Spring. Rejuvenation. Rebirth. Everything’s blooming. And, of course, people want free ebooks. With that in mind, here's a list of 10 free machine learning and data science titles to get your spring reading started right.

  https://www.kdnuggets.com/2017/04/10-free-must-read-books-machine-learning-data-science.html

• What Is Data Science, and What Does a Data Scientist Do?">What Is Data Science, and What Does a Data Scientist Do?

  This article is intended to help define the data scientist role, including typical skills, qualifications, education, experience, and responsibilities. This definition is somewhat loose, and given that the ideal experience and skill set is relatively rare to find in one individual.

  https://www.kdnuggets.com/2017/03/data-science-data-scientist-do.html

• What Top Firms Ask: 100+ Data Science Interview Questions

  Check this out: A topic wise collection of 100+ data science interview questions from top companies.

  https://www.kdnuggets.com/2017/03/top-firms-100-data-science-interview-questions.html

• Every Intro to Data Science Course on the Internet, Ranked">Every Intro to Data Science Course on the Internet, Ranked

  For this guide, I spent 10+ hours trying to identify every online intro to data science course offered as of January 2017, extracting key bits of information from their syllabi and reviews, and compiling their ratings.

  https://www.kdnuggets.com/2017/03/every-intro-data-science-course-ranked.html

• Introduction to Natural Language Processing, Part 1: Lexical Units

  This series explores core concepts of natural language processing, starting with an introduction to the field and explaining how to identify lexical units as a part of data preprocessing.

  https://www.kdnuggets.com/2017/02/datascience-introduction-natural-language-processing-part1.html

• 10 Tips to Improve your Data Science Interview

  Interviewing is a skill. Here are 10 tips and resources to improve your Data Science interviews.

  https://www.kdnuggets.com/2016/11/tips-improve-your-data-science-interview.html

• Deep Learning Research Review: Reinforcement Learning

  This edition of Deep Learning Research Review explains recent research papers in Reinforcement Learning (RL). If you don't have the time to read the top papers yourself, or need an overview of RL in general, this post has you covered.

  https://www.kdnuggets.com/2016/11/deep-learning-research-review-reinforcement-learning.html

• Top 10 Amazon Books in Data Mining, 2016 Edition">Top 10 Amazon Books in Data Mining, 2016 Edition

  Given the ongoing explosion in interest for all things Data Mining, Data Science, Analytics, Big Data, etc., we have updated our Amazon top books lists from last year. Here are the 10 most popular titles in the Data Mining category.

  https://www.kdnuggets.com/2016/11/top-10-amazon-books-data-mining.html

• Artificial Intelligence, Deep Learning, and Neural Networks, Explained">Artificial Intelligence, Deep Learning, and Neural Networks, Explained

  This article is meant to explain the concepts of AI, deep learning, and neural networks at a level that can be understood by most non-practitioners, and can also serve as a reference or review for technical folks as well.

  https://www.kdnuggets.com/2016/10/artificial-intelligence-deep-learning-neural-networks-explained.html

• Learning from Imbalanced Classes

  Imbalanced classes can cause trouble for classification. Not all hope is lost, however. Check out this article for methods in which to deal with such a situation.

  https://www.kdnuggets.com/2016/08/learning-from-imbalanced-classes.html

• The 10 Algorithms Machine Learning Engineers Need to Know">The 10 Algorithms Machine Learning Engineers Need to Know

  Read this introductory list of contemporary machine learning algorithms of importance that every engineer should understand.

  https://www.kdnuggets.com/2016/08/10-algorithms-machine-learning-engineers.html

• 7 Steps to Understanding Computer Vision

  A starting point for Computer Vision and how to get going deeper. Dive into this post for some overview of the right resources and a little bit of advice.

  https://www.kdnuggets.com/2016/08/seven-steps-understanding-computer-vision.html

• How to Start Learning Deep Learning

  Want to get started learning deep learning? Sure you do! Check out this great overview, advice, and list of resources.

  https://www.kdnuggets.com/2016/07/start-learning-deep-learning.html

• Bayesian Machine Learning, Explained">Bayesian Machine Learning, Explained

  Want to know about Bayesian machine learning? Sure you do! Get a great introductory explanation here, as well as suggestions where to go for further study.
   
   

  https://www.kdnuggets.com/2016/07/bayesian-machine-learning-explained.html

• History of Data Mining

  Data mining is a subfield of computer science which blends many techniques from statistics, data science, database theory and machine learning. Here are the major milestones and “firsts” in the history of data mining plus how it’s evolved and blended with data science and big data.

  https://www.kdnuggets.com/2016/06/rayli-history-data-mining.html

• 100 Active Blogs on Analytics, Big Data, Data Mining, Data Science, Machine Learning

  Stay on top of your data science skills game! Here’s a list of about 100 most active and interesting blogs on Big Data, Data Science, Data Mining, Machine Learning, and Artificial intelligence.

  https://www.kdnuggets.com/2016/03/100-active-blogs-analytics-big-data-science-machine-learning.html

• Introducing GraphFrames, a Graph Processing Library for Apache Spark

  An overview of Spark's new GraphFrames, a graph processing library based on DataFrames, built in a collaboration between Databricks, UC Berkeley's AMPLab, and MIT.

  https://www.kdnuggets.com/2016/03/introducing-graphframes-apache-spark.html

• Software development skills for data scientists

  Data science is not only about building the models and sharing insights, many times they have to collaborate in deploying models and sharing them with software developers, learn which things to keep in mind while doing so.

  https://www.kdnuggets.com/2015/12/software-development-skills-data-scientists.html

• The Best Advice From Quora on ‘How to Learn Machine Learning’

  Top machine learning writers on Quora give their advice on learning machine learning, including specific resources, quotes, and personal insights, along with some extra nuggets of information.

  https://www.kdnuggets.com/2015/10/learning-machine-learning-quora.html

• Crushed it! Landing a data science job

  Data scientist interviews depend on the company and the team, it might look like a software developer’s interview, or statistician’s interview. Here we collected some hot tips to pass along if you’re thinking about a move soon.

  https://www.kdnuggets.com/2015/10/erin-shellman-landing-data-science-job.html

• 15 Mathematics MOOCs for Data Science

  The essential mathematics necessary for Data Science can be acquired with these 15 MOOCs, with a strong emphasis on applied algebra & statistics.

  https://www.kdnuggets.com/2015/09/15-math-mooc-data-science.html

• A Great way to learn Data Science by simply doing it

  There are tons of great online resources out there we can pick up and learn them to become a master in data science. Here is a comprehensive list of data science course providers along with links to the data science courses.

  https://www.kdnuggets.com/2015/09/learn-data-science-by-doing.html

• How to become a Data Scientist for Free

  Here are the most required skills for a data scientist position based on ReSkill’s analyses of thousands of job posts and free resources to learn each skill.

  https://www.kdnuggets.com/2015/08/how-become-data-scientist-free.html

• Top 10 Data Mining Algorithms, Explained

  Top 10 data mining algorithms, selected by top researchers, are explained here, including what do they do, the intuition behind the algorithm, available implementations of the algorithms, why use them, and interesting applications.

  https://www.kdnuggets.com/2015/05/top-10-data-mining-algorithms-explained.html

• Deep Learning in a Nutshell – what it is, how it works, why care?

  Deep learning and neural networks are increasingly important concepts in computer science with great strides being made by large companies like Google and startups like DeepMind.

  https://www.kdnuggets.com/2015/01/deep-learning-explanation-what-how-why.html

• Statistics Software

  commercial | free Analyse-it!, accurate low-cost statistical software for Microsoft Excel. Appricon's Analysis Studio, a statistical analysis and modeling software with advanced logistic regression modeling, Read more »

  https://www.kdnuggets.com/software/statistics.html

• Blogs on AI, Analytics, Data Science, Machine Learning

  Here are some of the most interesting and regularly-updated blogs on Analytics, Big Data, Data Science, Data Mining, and Machine Learning, in alphabetical order. Blog Read more »

  https://www.kdnuggets.com/websites/blogs.html

• KDnuggets™ News 13:n19, Aug 7

  Features (9) | Software (5) | Webcasts (3) | Courses, Events (1) | Meetings (3) | Jobs (3) | Academic (1) | Competitions (3) | Publications Read more »

  https://www.kdnuggets.com/2013/n19.html