- Inside DeepMind’s New Efforts to Use Deep Learning to Advance Mathematics - Dec 10, 2021.
Using deep learning techniques can help mathematicians develop intuitions about the toughest problems in the field.
Deep Learning, DeepMind, Mathematics
- OpenAI’s Approach to Solve Math Word Problems - Nov 9, 2021.
OpenAI's latest research aims to solve math word problems. Let's dive a bit deeper into the ideas behind this new research.
GPT-3, Mathematics, NLP, OpenAI
- How to do “Limitless” Math in Python - Oct 7, 2021.
How to perform arbitrary-precision computation and much more math (and fast too) than what is possible with the built-in math library in Python.
Linear Algebra, Mathematics, Probability, Python, Statistics
Path to Full Stack Data Science - Sep 27, 2021.
Start your journey toward mastering all aspects of the field of Data Science with this focused list of in-depth self-learning resources. Curated with the beginner in mind, these recommendations will help you learn efficiently, and can also offer existing professionals useful highlights for review or help filling in any gaps in skills.
Career Advice, Data Science, Data Science Education, Data Visualization, Mathematics, Python, R, Roadmap
- Math 2.0: The Fundamental Importance of Machine Learning - Sep 8, 2021.
Machine learning is not just another way to program computers; it represents a fundamental shift in the way we understand the world. It is Math 2.0.
AI, Machine Learning, Mathematics
- How Machine Learning Leverages Linear Algebra to Solve Data Problems - Sep 7, 2021.
Why you should learn the fundamentals of linear algebra.
Data Science, Linear Algebra, Machine Learning, Mathematics
Learning Data Science and Machine Learning: First Steps After The Roadmap - Aug 24, 2021.
Just getting into learning data science may seem as daunting as (if not more than) trying to land your first job in the field. With so many options and resources online and in traditional academia to consider, these pre-requisites and pre-work are recommended before diving deep into data science and AI/ML.
Data Science, Machine Learning, Mathematics, Python, Roadmap, Statistics
- Linear Algebra for Natural Language Processing - Aug 17, 2021.
Learn about representing word semantics in vector space.
Linear Algebra, Mathematics, NLP, Python
- Essential Math for Data Science: Introduction to Systems of Linear Equations - Aug 6, 2021.
In this post, you’ll see how you can use systems of equations and linear algebra to solve a linear regression problem.
Data Science, Linear Algebra, Mathematics
- Essential Math for Data Science: Basis and Change of Basis - May 28, 2021.
In this article, you will learn what the basis of a vector space is, see that any vectors of the space are linear combinations of the basis vectors, and see how to change the basis using change of basis matrices.
Data Science, Linear Algebra, Mathematics
Essential Linear Algebra for Data Science and Machine Learning - May 10, 2021.
Linear algebra is foundational in data science and machine learning. Beginners starting out along their learning journey in data science--as well as established practitioners--must develop a strong familiarity with the essential concepts in linear algebra.
Data Science Education, Data Visualization, Linear Algebra, Linear Regression, Mathematics, Python
3 Mathematical Laws Data Scientists Need To Know - Mar 2, 2021.
Machine learning and data science are founded on important mathematics in statistics and probability. A few interesting mathematical laws you should understand will especially help you perform better as a Data Scientist, including Benford's Law, the Law of Large Numbers, and Zipf's Law.
Benford's Law, Data Science, Mathematics, Zipf's Law
- Essential Math for Data Science: Scalars and Vectors - Feb 12, 2021.
Linear algebra is the branch of mathematics that studies vector spaces. You’ll see how vectors constitute vector spaces and how linear algebra applies linear transformations to these spaces. You’ll also learn the powerful relationship between sets of linear equations and vector equations.
Data Science, Linear Algebra, Mathematics
Essential Math for Data Science: Introduction to Matrices and the Matrix Product - Feb 5, 2021.
As vectors, matrices are data structures allowing you to organize numbers. They are square or rectangular arrays containing values organized in two dimensions: as rows and columns. You can think of them as a spreadsheet. Learn more here.
Data Science, Linear Algebra, Mathematics, numpy, Python
Essential Math for Data Science: Information Theory - Jan 15, 2021.
In the context of machine learning, some of the concepts of information theory are used to characterize or compare probability distributions. Read up on the underlying math to gain a solid understanding of relevant aspects of information theory.
Data Science, Mathematics
- Essential Math for Data Science: The Poisson Distribution - Dec 29, 2020.
The Poisson distribution, named after the French mathematician Denis Simon Poisson, is a discrete distribution function describing the probability that an event will occur a certain number of times in a fixed time (or space) interval.
Data Science, Distribution, Mathematics, Poisson Distribution
- Matrix Decomposition Decoded - Dec 11, 2020.
This article covers matrix decomposition, as well as the underlying concepts of eigenvalues (lambdas) and eigenvectors, as well as discusses the purpose behind using matrix and vectors in linear algebra.
Linear Algebra, Mathematics, numpy, PCA, Python
- Essential Math for Data Science: Probability Density and Probability Mass Functions - Dec 7, 2020.
In this article, we’ll cover probability mass and probability density function in this sample. You’ll see how to understand and represent these distribution functions and their link with histograms.
Data Science, Mathematics, Probability, Statistics
- Essential Math for Data Science: Integrals And Area Under The Curve - Nov 25, 2020.
In this article, you’ll learn about integrals and the area under the curve using the practical data science example of the area under the ROC curve used to compare the performances of two machine learning models.
Machine Learning, Mathematics, Metrics, numpy, Python, Unbalanced
- Math for Programmers - Sep 10, 2020.
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. Save 50% with code kdmath50.
Book, Manning, Mathematics, Programming
Modern Data Science Skills: 8 Categories, Core Skills, and Hot Skills - Sep 8, 2020.
We analyze the results of the Data Science Skills poll, including 8 categories of skills, 13 core skills that over 50% of respondents have, the emerging/hot skills that data scientists want to learn, and what is the top skill that Data Scientists want to learn.
Communication, Data Preparation, Data Science Skills, Data Visualization, Excel, GitHub, Mathematics, Poll, Python, Reinforcement Learning, scikit-learn, SQL, Statistics
These Data Science Skills will be your Superpower - Aug 20, 2020.
Learning data science means learning the hard skills of statistics, programming, and machine learning. To complete your training, a broader set of soft skills will round out your capabilities as an effective and successful professional Data Scientist.
Communication, Data Preparation, Data Science Skills, Data Visualization, Mathematics, Statistics
- Math for Programmers! - Jul 30, 2020.
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. Save 50% with code kdmath50.
Book, Manning, Mathematics, Programming
- Math and Architectures of Deep Learning! - Jul 15, 2020.
This hands-on book bridges the gap between theory and practice, showing you the math of deep learning algorithms side by side with an implementation in PyTorch. Save 50% with code kdarch50.
Architecture, Deep Learning, Manning, Mathematics, PyTorch
- KDnuggets™ News 20:n25, Jun 24: PyTorch Fundamentals You Should Know; Free Math Courses to Boost Your Data Science Skills - Jun 24, 2020.
A Classification Project in Machine Learning: a gentle step-by-step guide; Crop Disease Detection Using Machine Learning and Computer Vision; Bias in AI: A Primer; Machine Learning in Dask; How to Deal with Missing Values in Your Dataset
Agriculture, Computer Vision, Courses, Data Science, Machine Learning, Mathematics, PyTorch, Tom Fawcett
4 Free Math Courses to do and Level up your Data Science Skills - Jun 22, 2020.
Just as there is no Data Science without data, there's no science in data without mathematics. Strengthening your foundational skills in math will level you up as a data scientist that will enable you to perform with greater expertise.
Bayesian, Coursera, edX, Inference, Linear Algebra, Mathematics, Online Education, Principal component analysis, Probability, Python, Statistics
- Math and Architectures of Deep Learning - Jun 11, 2020.
This hands-on book bridges the gap between theory and practice, showing you the math of deep learning algorithms side by side with an implementation in PyTorch. Save 40% off Math and Architectures of Deep Learning with code nlkdarch40
Deep Learning, Manning, Mathematics
A Concise Course in Statistical Inference: The Free eBook - Apr 27, 2020.
Check out this freely available book, All of Statistics: A Concise Course in Statistical Inference, and learn the probability and statistics needed for success in data science.
Book, Free ebook, Mathematics, Statistics
- Math and Architectures of Deep Learning - Apr 22, 2020.
This hands-on book bridges the gap between theory and practice, showing you the math of deep learning algorithms side by side with an implementation in PyTorch. You can save 40% off Math and Architectures of Deep Learning until May 13! Just enter the code nlkdarch40 at checkout when you buy from manning.com.
Deep Learning, Manning, Mathematics
- Math for Programmers! - Mar 11, 2020.
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.
Book, Manning, Mathematics, Programming
- Data Science Curriculum for self-study - Feb 26, 2020.
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.
Advice, Data Science, Data Science Education, Data Visualization, Mathematics, Probability, Programming, Statistics
Free Mathematics Courses for Data Science & Machine Learning - Feb 25, 2020.
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.
Courses, Data Science, Machine Learning, Mathematics, MOOC
- Fourier Transformation for a Data Scientist - Feb 14, 2020.
The article contains a brief intro into Fourier transformation mathematically and its applications in AI.
Data Science, Data Scientist, Mathematics, Python
Math for Programmers – your guide for solving math problems in code - Feb 12, 2020.
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.
Book, Manning, Mathematics, Programming
- Intro to Machine Learning and AI based on high school knowledge - Feb 5, 2020.
Machine learning information is becoming pervasive in the media as well as a core skill in new, important job sectors. Getting started in the field can require learning complex concepts, and this article outlines an approach on how to begin learning about these exciting topics based on high school knowledge.
AI, Beginners, Linear Regression, Machine Learning, Mathematics
Math for Programmers! - Jan 15, 2020.
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.
Book, Manning, Mathematics, Programming
- The Math Behind Bayes - Nov 19, 2019.
This post will be dedicated to explaining the maths behind Bayes Theorem, when its application makes sense, and its differences with Maximum Likelihood.
Bayes Theorem, Mathematics, Probability
- Lagrange multipliers with visualizations and code - Aug 6, 2019.
In this story, we’re going to take an aerial tour of optimization with Lagrange multipliers. When do we need them? Whenever we have an optimization problem with constraints.
Analytics, Mathematics, Optimization, Python
- Probability Mass and Density Functions - May 21, 2019.
This content is part of a series about the chapter 3 on probability from the Deep Learning Book by Goodfellow, I., Bengio, Y., and Courville, A. (2016). It aims to provide intuitions/drawings/python code on mathematical theories and is constructed as my understanding of these concepts.
Pages: 1 2
Mathematics, Probability, Statistics
- Math for Machine Learning - Jan 4, 2019.
This ebook explains the math involved and introduces you directly to the foundational topics in machine learning.
Book, ebook, Machine Learning, Mathematics, Richard Han
- A comprehensive list of Machine Learning Resources: Open Courses, Textbooks, Tutorials, Cheat Sheets and more - Dec 7, 2018.
A thorough collection of useful resources covering statistics, classic machine learning, deep learning, probability, reinforcement learning, and more.
Cheat Sheet, Data Science Education, Deep Learning, Machine Learning, Mathematics, Open Source, Reinforcement Learning, Resources, Statistics
- Preprocessing for Deep Learning: From covariance matrix to image whitening - Oct 10, 2018.
The goal of this post/notebook is to go from the basics of data preprocessing to modern techniques used in deep learning. My point is that we can use code (Python/Numpy etc.) to better understand abstract mathematical notions!
Pages: 1 2 3
Data Preprocessing, Deep Learning, Image Processing, Mathematics
Machine Learning Cheat Sheets - Sep 11, 2018.
Check out this collection of machine learning concept cheat sheets based on Stanord CS 229 material, including supervised and unsupervised learning, neural networks, tips & tricks, probability & stats, and algebra & calculus.
Cheat Sheet, Deep Learning, Machine Learning, Mathematics, Neural Networks, Probability, Statistics, Supervised Learning, Tips, Unsupervised Learning
Unveiling Mathematics Behind XGBoost - Aug 14, 2018.
Follow me till the end, and I assure you will atleast get a sense of what is happening underneath the revolutionary machine learning model.
Gradient Boosting, Mathematics, XGBoost
- Math for Machine Learning: Open Doors to Data Science and Artificial Intelligence - Jul 18, 2018.
This ebook explains the math involved and introduces you directly to the foundational topics in machine learning.
ebook, Machine Learning, Mathematics, Richard Han
- Learn AI and Data Science rapidly based only on high school math – KDnuggets Offer - May 25, 2018.
This 3-month program, created by Ajit Jaokar, who teaches at Oxford, is interactive and delivered by video. Coding examples are in Python. Places limited - check special KDnuggets rate.
AI, Ajit Jaokar, Data Science Education, Mathematics, Online Education, Python
Boost your data science skills. Learn linear algebra. - May 3, 2018.
The aim of these notebooks is to help beginners/advanced beginners to grasp linear algebra concepts underlying deep learning and machine learning. Acquiring these skills can boost your ability to understand and apply various data science algorithms.
Data Science, Linear Algebra, Mathematics, numpy, Python
7 Books to Grasp Mathematical Foundations of Data Science and Machine Learning - Apr 17, 2018.
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.
Book, Data Science, Ian Goodfellow, Machine Learning, Mathematics, Robert Tibshirani, Vladimir Vapnik
Data Structures Related to Machine Learning Algorithms - Jan 30, 2018.
If you want to solve some real-world problems and design a cool product or algorithm, then having machine learning skills is not enough. You would need good working knowledge of data structures.
Pages: 1 2
Machine Learning, Mathematics, Programming, Statsbot
How Much Mathematics Does an IT Engineer Need to Learn to Get Into Data Science? - Dec 20, 2017.
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.
Data Science, Engineer, Machine Learning, Mathematics
- Practical skills that practical data scientists need - May 13, 2016.
The long story short, data scientist needs to be capable of solving business analytics problems. Learn more about the skill-set you need to master to achieve so.
Business Context, Data Scientist, Mathematics, Skills, SQL
- The Evolution of the Data Scientist - Mar 16, 2016.
We trace the evolution of Data Science from ancient mathematics to statistics and early neural networks, to present successes like AlphaGo and self-driving car, and look into the future.
Automated, Data Scientist, Demis Hassabis, Evolution, Mathematics, Statistics
- How to Tackle a Lottery with Mathematics - Jan 27, 2016.
With mathematical rigor and narrative flair, Adam Kucharski reveals the tangled history of betting and science. The house can seem unbeatable. In this book, Kucharski shows us just why it isn't. Even better, he shows us how the search for the perfect bet has been crucial for the scientific pursuit of a better world.
Lottery, Mathematics
- 15 Mathematics MOOCs for Data Science - Sep 23, 2015.
The essential mathematics necessary for Data Science can be acquired with these 15 MOOCs, with a strong emphasis on applied algebra & statistics.
Pages: 1 2
Applied Statistics, Coursera, Data Science, edX, Mathematics, MOOC, R, Udemy
- Deep Learning and the Triumph of Empiricism - Jul 7, 2015.
Theoretical guarantees are clearly desirable. And yet many of today's best-performing supervised learning algorithms offer none. What explains the gap between theoretical soundness and empirical success?
Big Data, Data Science, Deep Learning, Mathematics, Statistics, Zachary Lipton
- Poincare Conjecture, Perelman way, and Topology of social networks - May 3, 2014.
We examine the connections between the $1 million proof of Poincare conjecture by a reclusive math genius and the topological behavior and information diffusion over social networks.
Mathematics, Social Networks, Topology
