BeOptimized Library


Passionate about SAS Code and Python, we stay up-to-date regarding the latest developments thanks to the SAS training, the SAS Support , the SUGI , the SAS Global Forum, SASENSEI, the SAS Belux User group or the SAS communities.

This page contains interesting papers we collected throught the Web and are used for our coaching preparations and our specific consultancy activities. Download them for free and read them where you want!!!

Publication list

Python keras

This paper is a cheat sheet talking about Keras. Keras is a powerful and easy-to-use deep learning library for Theano and TensorFlow that provides a high-level neural networks API to develop and evaluate deep learning models.

Python Scikit-Learn

This paper is a cheat sheet talking about Scikit-learn. Scikit-learn is an open source Python library that implements a range of machine learning, preprocessing, cross-validation and visualization algorithms using a unified interface.

Python SciPy

This paper is a cheat sheet talking about SciPy. The SciPy library is one of the core packages for scientific computing that provides mathematical algorithms and convenience functions built on the NumPy extension of Python

Linear Regression in Python

Linear regression is one of the fundamental statistical and machine learning technique. This paper talk about linear regression with Python: definition, packages, examples, how to implement

Data Science with Python

This paper, written by Afshine Amidi & Shervine Amidi from Massachusetts Institute of Technology, is a short python summary on some useful fonctionnality applied to data manipulation: file management, filtering, datetime conversion, concatenation, aggregation and windows function

Machine learning with Python

This pdf is a Machine Learning tutorial (167p) created by Tutorials Point and published on LinkedIn. In this book you will learn the basics of Python and Pandas and the main ML algorithms (Regression, Decision tree, clustering, and so on). The book provides examples and explain step by step why they are using the codes.

Learning SciPy for Numerical and Scientific Computing

This pdf is a turorial (150p) published by packt and found on LinkedIn. If you read this e-book you will learn how to use SciPy for linear algebra, numerical analysis, signal processing, data mining and computational geometry. You need a good mathematical background and couple of coffee mugs.

Machine Learning Interview Cheat sheets

This pdf explain, in short, the theory behind each ML algorithms. They provide the definition, mathematical formula , graphics, and so on. It's not orianted to a specific programming language, just theory. Very useful to use before an interview or an exam or just to remember how it works.

Machine Learning with K-Nearest Neighbors

K-nearest neighbors is a supervised classification and regression machine learning algorithm. This e-book of 24 pages explains you the theory behind the algorithm, discuss how it works, pros and cons and make the difference beween Manhattan, Euclidian, Minkowski distance

Real World Machine Learning

This 250 p pdf is an e-book edited by Manning and found on LinkedIn. They EXPLAIN basic and advanced ML algorithms with Python and provide a practical workflow and real life examples (eg: tipping behavior of NYC taxis, employee business rules, and so on). This books also explain topics on NLP, image and time series analysis.

Hypothesis testing: A Visual Introduction To Statistical Significance

This 137 p e-book found on LinkedIn provides you an easy to read summary on statistical concepts and tests like Normal curve, Z test, T test, Paired T test and discuss what we have to do with unequal variance.

Data Science Cheat Sheet

This pdf is a cheat sheet summary in 5 pages on the main ML algorithms. For each of them, there are explanation, graphical representation and some formula. Well done !

TensorFlow2 Cheat Sheet

TensorFlow is an open-source software library for high performance numerical computation. This pdf is a cheat sheet

Python Data Science handbook

This e-book is the official Python Data Science Handbook of Oreilly. I found it on linkedin. It explain Numpy, Data manipulation with Pandas, Visualization with Matplotlib and some ML algorithms

This site uses cookies. .

By continuing to browse the site you are agreeing to our use of cookies. Review our cookies information for more details.