 Hadrien Jean owns a Ph.D in cognitive science and works as a machine learning scientist specialized in sound and education. He wrote a series of tutorials as notes of the Deep Learning Book from Ian Goodfellow helping thousands of people to learn math for machine learning. He's also working on speech processing and leads projects on biodiversity assessment using deep learning applied to audio recordings. He concurrently teaches machine learning and deep learning in data science bootcamps at Le Wagon.

 Essential Math for Data Science: Eigenvectors and Application to PCA By Hadrien Jean, Machine Learning Scientist on June 28, 2022 in Data ScienceIn this article, you’ll learn about the eigendecomposition of a matrix. Essential Math for Data Science: Visual Introduction to Singular Value Decomposition By Hadrien Jean, Machine Learning Scientist on June 21, 2022 in Data ScienceThis article will cover singular value decomposition (SVD), which is a major topic of linear algebra, data science, and machine learning. Essential Math for Data Science: Introduction to Systems of Linear Equations By Hadrien Jean, Machine Learning Scientist on August 6, 2021 in Data Science, Linear Algebra, MathematicsIn this post, you’ll see how you can use systems of equations and linear algebra to solve a linear regression problem. Essential Math for Data Science: Basis and Change of Basis By Hadrien Jean, Machine Learning Scientist on May 28, 2021 in Data Science, Linear Algebra, MathematicsIn 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. Essential Math for Data Science: Scalars and Vectors By Hadrien Jean, Machine Learning Scientist on February 12, 2021 in Data Science, Linear Algebra, MathematicsLinear 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.  Essential Math for Data Science: Introduction to Matrices and the Matrix Product By Hadrien Jean, Machine Learning Scientist on February 5, 2021 in Data Science, Linear Algebra, Mathematics, numpy, PythonAs 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.  Essential Math for Data Science: Information Theory By Hadrien Jean, Machine Learning Scientist on January 15, 2021 in Data Science, MathematicsIn 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. Essential Math for Data Science: The Poisson Distribution By Hadrien Jean, Machine Learning Scientist on December 29, 2020 in Data Science, Distribution, Mathematics, Poisson DistributionThe 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. Essential Math for Data Science: Probability Density and Probability Mass Functions By Hadrien Jean, Machine Learning Scientist on December 7, 2020 in Data Science, Mathematics, Probability, StatisticsIn 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. Essential Math for Data Science: Integrals And Area Under The Curve By Hadrien Jean, Machine Learning Scientist on November 25, 2020 in Machine Learning, Mathematics, Metrics, numpy, Python, UnbalancedIn 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. Get the FREE ebook 'The Great Big Natural Language Processing Primer' and 'The Complete Collection of Data Science Cheat Sheets' along with the leading newsletter on Data Science, Machine Learning, AI & Analytics straight to your inbox. 