Research Guides: Data Science: Computational Analytics

Other Guides

Fuzzy Sets-Based Methods and Techniques for Modern Analytics by Ali Ebrahimnejad; José Luis Verdegay The book offers a comprehensive, practice-oriented introduction to the field of fuzzy mathematical programming (FMP) as key topic of modern analytics. FMP plays a fundamental role in dealing with a varied range of problems, such as those concerning smart cities, sustainability, and renewable energies. This book includes an introduction to the basic concepts, together with extensive information on the computational-intelligence-based optimization models and techniques that have been used to date. Special emphasis is given to fuzzy transportation problems. The book is a valuable resource for researchers, data scientists and practitioners dealing with computational-intelligence-based optimization models for analytics.
ISBN: 9783319739021
Publication Date: 2018-03-08
Immersive Analytics by Kim Marriott, Falk Schreiber, Tim Dwyer, Karsten Klein, Nathalie Henry Riche, Takayuki Itoh, Wolfgang Stuerzlinger, Bruce H. Thomas
ISBN: 9783030013882
Publication Date: 2018

Papers with Code
The mission of Papers With Code is to create a free and open resource with Machine Learning papers, code and evaluation tables.

Scikit-learn
Supports many supervised and unsupervised learning algorithms. Examples include linear and logistic regressions, decision trees, clustering, k-means and so on. It builds on two basic libraries of Python, NumPy and SciPy.
TensorFlow
Used by Google to identify objects in photos or understand spoken words in its voice-recognition app. When you write a program in Python, you can compile and run on either your CPU or GPU.
Theano
Theano is similar to NumPy. Theano allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. What sets Theano apart is that it takes advantage of the computer’s GPU.
Pyevolve
Framework to build and execute genetic algorithms
Pattern
Good for: NLP, clustering, and classification. The data mining portion helps you collect data from web services like Google, Twitter, and Wikipedia. It also has a web crawler and HTML DOM parser.

TensorFlow
Used by Google to identify objects in photos or understand spoken words in its voice-recognition app. When you write a program in Python, you can compile and run on either your CPU or GPU.
Sparklyr
sparklyr allows you to access the machine learning routines provided by the spark.ml package together with sparklyr’s dplyr interface
Tidymodels
caret
Used for classification and regression training. The task of this CARET package is to integrate the training and prediction of a model.
randomForest
Can be employed for solving regression and classification tasks. Additionally, it can be used for training missing values and outliers.
e1071
Implements support vector machines (SVM), shortest path computation, bagged clustering, Naive Bayes classifier, short-time Fourier transform, fuzzy clustering, etc.