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The Inescapable Conclusion: Machine Learning Is Not Like Your Brain
The final article in this nine-part series summarizes the many reasons why Machine Learning is not like your brain - along with a few similarities.
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Multimodal Grounded Learning with Vision and Language
How to enable AI models to have similar capabilities: to communicate, to ground, and to learn from language.
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What is Chebychev’s Theorem and How Does it Apply to Data Science?
Chebyshev’s Theorem applies to every data set and is heavily used by Statisticians, Data Scientists, and Machine Learning Engineers.
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Linux for Data Science Cheatsheet
KDnuggets is back with another exclusive cheatsheet, this time sharing a Linux quick reference for data science.
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How Much Math Do You Need in Data Science?
There exist so many great computational tools available for Data Scientists to perform their work. However, mathematical skills are still essential in data science and machine learning because these tools will only be black-boxes for which you will not be able to ask core analytical questions without a theoretical foundation.
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Telling a Great Data Story: A Visualization Decision Tree
Pick your visualizations strategically. They need to tell a story.
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Will Poor-Quality Data Undermine your Business?
Leverage precise data to discover business opportunities, make strategic decisions, and increase ROI with a powerful data quality platform.
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10 Most Common Data Quality Issues and How to Fix Them
Ensuring data quality guarantees more data-informed decisions. Hence, this article highlights the common data quality issues and ways to overcome them.
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Picking Examples to Understand Machine Learning Model
Understanding ML by combining explainability and sample picking.
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Top Posts November 14-20: Git for Data Science Cheatsheet
Git for Data Science Cheatsheet • 6 Best Free Online Courses to Learn Python and Boost Your Career • How to Select Rows and Columns in Pandas Using [ ], .loc, iloc, .at and .iat • How LinkedIn Uses Machine Learning To Rank Your Feed • 7 SQL Concepts You Should Know For Data Science
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Announcing a Blog Writing Contest, Winner Gets an NVIDIA GPU!
KDnuggets and NVIDIA are announcing a blog-writing contest with a GPU focus, with the winner receiving an RTX 3080 Ti GPU!
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How to Use Graph Theory to Scout Soccer
Take Soccer Analytics to the Next Level with Graph Theory: Here’s What to Know and How to Do It.
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New From Anaconda! Data Science Training and Cloud Hosted Notebooks
Anaconda is incredibly excited to announce the release of a brand-new suite of products on the Anaconda Nucleus platform: Anaconda Notebooks and Anaconda Learning.
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Introduction to Pandas for Data Science
The Pandas library is core to any Data Science work in Python. This introduction will walk you through the basics of data manipulating, and features many of Pandas important features.
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7 SQL Concepts You Should Know For Data Science
The post explains all the key elements of SQL that you must know as a data science practitioner.
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Research Papers for NLP Beginners
Read research papers on neural models, word embedding, language modeling, and attention & transformers.
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Geocoding in Python: A Complete Guide
A step-by-step tutorial on geocoding with Python
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9 Free Resources to Master Python
Python is the most popular general-purpose language and you can learn it for free.
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How to Setup Julia on Jupyter Notebook
Learn three simple steps to install Julia for Jupyter Notebook and write your first data visualization code.
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What To Expect for AI Quality Trends In 2023
Based on the recent discussions with dozens of Fortune 500 data science teams, we can expect to see a continued spotlight on AI model quality in 2023.
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KDnuggets Top Posts for October 2022: 10 Cheat Sheets You Need To Ace Data Science Interview
10 Cheat Sheets You Need To Ace Data Science Interview • 7 Free Platforms for Building a Strong Data Science Portfolio • The Complete Free PyTorch Course for Deep Learning • 3 Valuable Skills That Have Doubled My Income as a Data Scientist • 25 Advanced SQL Interview Questions for Data Scientists • A Data Science Portfolio That Will Land You The Job in 2022 • Top Free Git GUI Clients for Beginners • Essential Books You Need to Become a Data Engineer
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If I Had To Start Learning Data Science Again, How Would I Do It?
While different ways to learn Data Science for the first time exist, the approach that works for you should be based on how you learn best. One powerful method is to evolve your learning from simple practice into complex foundations, as outlined in this learning path recommended by a physicist who turned into a Data Scientist.
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KDnuggets News, November 16: How LinkedIn Uses Machine Learning • Confusion Matrix, Precision, and Recall Explained
How LinkedIn Uses Machine Learning To Rank Your Feed • Confusion Matrix, Precision, and Recall Explained • Matrix Multiplication for Data Science (or Machine Learning) • Machine Learning from scratch: Decision Trees • 7 Python Projects for Beginners
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Git for Data Science Cheatsheet
Knowing git is no longer an option for data professionals. Grab this handy reference sheet now and make sure you know how to git the job done.
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6 Best Free Online Courses to Learn Python and Boost Your Career
The demand for Data Scientists who are proficient in Python is at an all time high. Python has helped people boost their careers in finance, consulting, research, software tech, and robotics. Explore 6 courses designed to help you learn Python.
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Efficiency Spells the Difference Between Biological Neurons and Their Artificial Counterparts
Part 8 of the series explores a single facet of biological neurons which, so far, have kept them way ahead of their artificial counterparts: their efficiency.
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Top Data Analyst Certification Courses for 2022
Top certification courses by IBM, Edureka, DataCamp, Udacity, and Google.
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5 Linguistics Courses for NLP Practitioners
This collection of 5 courses is intended to help NLP practitioners or hopefuls acquire some of their lacking linguistics knowledge.
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How LinkedIn Uses Machine Learning To Rank Your Feed
In this post, you will learn to clarify business problems & constraints, understand problem statements, select evaluation metrics, overcome technical challenges, and design high-level systems.
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A Quick Overview of Voronoi Diagrams
If you've heard of Voronoi diagrams but don't klnow what they are, have a look at this quick and informative overview.
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Top Posts November 7-13: How to Select Rows and Columns in Pandas
How to Select Rows and Columns in Pandas • Confusion Matrix, Precision, and Recall Explained • Decision Tree Algorithm, Explained • Matrix Multiplication for Data Science (or Machine Learning) • The Most Comprehensive List of Kaggle Solutions and Ideas
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5 Ways of Filtering Python Lists
Filter the list elements using for loop, list comprehension, regex, filter(), and lambda functions.
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Machine Learning from Scratch: Decision Trees
A simple explanation and implementation of DTs ID3 algorithm in Python
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Matrix Multiplication for Data Science (or Machine Learning)
Learn the math behind matrix multiplication for data science and machine learning with code examples.
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How To Create An Effective AI Strategy
This post elaborates on various factors that go into consideration while prioritizing various AI initiatives.
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Understanding Bias-Variance Trade-Off in 3 Minutes
This article is the write-up of a Machine Learning Lighting Talk, intuitively explaining an important data science concept in 3 minutes.
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Getting Started with PyCaret
An open-source low-code machine learning library for training and deploying the models in production.
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7 Python Projects for Beginners
Simple and fun Python projects to get experience and build a strong portfolio.
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KDnuggets News, November 9: 7 Tips To Produce Readable Data Science Code • 30 Resources for Mastering Data Visualization
7 Tips To Produce Readable Data Science Code • 30 Resources for Mastering Data Visualization • 15 More Free Machine Learning and Deep Learning Books • Simple and Fast Data Streaming for Machine Learning Projects • The AI Education Gap and How to Close It
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Watch all of IMPACT’s breakout sessions ON-DEMAND
Good news! You can now watch all of IMPACT's breakout sessions ON-DEMAND.
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Analyzing Diversity & Inclusion with SQL
The most underrated SQL function for analyzing diversity.
By Josh Berry, Leads Customer Facing Data Science at Rasgo on November 9, 2022 in SQL
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Finally a Book on Attention!
Finally a book on Attention. Learn how to build your own transformer model with Machine Learning Mastery's new book.
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Confusion Matrix, Precision, and Recall Explained
Learn these key machine learning performance metrics to ace data science interviews.
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Map out your journey towards SAS Certification
Nearly 50% of certification holders said it was easier to find new jobs, enter new career fields and land job interviews. Read on to learn about every resource you’ll need from start to finish to receive your SAS certification.
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Python Control Flow Cheatsheet
The latest KDnuggets cheatsheet focuses on Python flow control, how we manage the execution order of statements in a program. Check it out for a quick start.
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The Most Comprehensive List of Kaggle Solutions and Ideas
Learn from top-performing teams in the competition to get better at understanding machine learning techniques.
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3 Useful Python Automation Scripts
The post highlights three useful applications of using python to automate simple desktop tasks. Stay tuned till the end of the post to find the reference for a bonus resource.
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Approaches to Text Summarization: An Overview
This article will present the main approaches to text summarization currently employed, as well as discuss some of their characteristics.
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15 More Free Machine Learning and Deep Learning Books
Check out this second list of 15 FREE ebooks for learning machine learning and deep learning.
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Top Posts October 31 – November 6: How to Select Rows and Columns in Pandas
How to Select Rows and Columns in Pandas Using [ ], .loc, iloc, .at and .iat • 15 Free Machine Learning and Deep Learning Books • Decision Tree Algorithm, Explained • Should I Learn Julia? • 7 Techniques to Handle Imbalanced Data
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4 Ways to Rename Pandas Columns
A simple pandas tutorial for beginners with code examples.
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The Ultimate Guide To Different Word Embedding Techniques In NLP
A machine can only understand numbers. As a result, converting text to numbers, called embedding text, is an actively researched topic. In this article, we review different word embedding techniques for converting text into vectors.
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Attend the Data Science Symposium 2022, November 8 in Cincinnati
The Center for Business Analytics at the University of Cincinnati will present its annual Data Science Symposium 2022 on November 8. This all day in-person event will have three featured speakers and two tech talk tracks with four concurrent presentations in each track. The event, held at the Lindner College of Business, is open to all.
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The AI Education Gap and How to Close It
AI education is broken, how do we solve it? Individuals end up learning a specific tool or tactic in a vacuum. They are missing the real-world applicability and collaboration that is critical to building impactful AI solutions in line with the organization’s strategy.
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What is Statistical Skew?
Read this overview of what is skewness, and how to calculate it.
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Simple and Fast Data Streaming for Machine Learning Projects
Learn about the cutting-edge DagsHub's Direct Data Access for simple and faster data loading and model training.
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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.
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9 Skills You Need to Become a Data Engineer
A data engineer is a fast-growing profession with amazing challenges and rewards. Which skills do you need to become a data engineer? In this post, we’ll take a look at both hard and soft skills.
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KDnuggets News, November 2: The Current State of Data Science Careers • 15 Free Machine Learning and Deep Learning Books
The Current State of Data Science Careers • 15 Free Machine Learning and Deep Learning Books • How to Make Python Code Run Incredibly Fast • Machine Learning on the Edge • Don't Become a Commoditized Data Scientist
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30 Resources for Mastering Data Visualization
Want to master data visualization? This list of 30 resources and tools will help you get started on your path toward mastering data visualization.
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7 Tips To Produce Readable Data Science Code
In this article, we will go over a few steps that you can take to produce readable, high-quality code.
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365 Data Science courses free until November 21
The unlimited access initiative provides a risk-free way to break into data science.
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Random Forest vs Decision Tree: Key Differences
Check out this reasoned comparison of 2 critical machine learning algorithms to help you better make an informed decision.
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Getting Started with spaCy for NLP
In this blog, we will explore how to get started with spaCy right from the installation to explore the various functionalities it provides.
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Should I Learn Julia?
Do you think learning Julia is better for your data science career? Let’s find out.
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Top Posts October 24-30: How to Select Rows and Columns in Pandas
How to Select Rows and Columns in Pandas Using [ ], .loc, iloc, .at and .iat • Decision Tree Algorithm, Explained • Graphs: The natural way to understand data • 7 Techniques to Handle Imbalanced Data • A Data Science Portfolio That Will Land You The Job in 2022
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The Gap Between Deep Learning and Human Cognitive Abilities
How do we bridge this gap between deep learning and human cognitive ability?
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15 Free Machine Learning and Deep Learning Books
Check out this list of 15 FREE ebooks for learning machine learning and deep learning.
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Don’t Become a Commoditized Data Scientist
Unicorns don't exist. Aim instead to be an endangered species.
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How to Make Python Code Run Incredibly Fast
In this article, I have explained some tips and tricks to optimize and speed up Python code.
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The Current State of Data Science Careers
If you’re someone in data science or aiming to get into a data science career, this article will give you a comprehensive analysis of the state of the field.
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