Product Details
Meta-Analytics: Consensus Approaches and System Patterns for Data Analysis
Free Shipping+Easy returns
Product Details
From Sunflowers to Growth Patterns: Data Representation and Analysis
Free Shipping+Easy returns
Product Details
Topological Data Analysis for Scientific Visualization (Mathematics and Visualization)
Free Shipping+Easy returns
Product Details
Kernel Methods for Pattern Analysis
Free Shipping+Easy returns
Product Details
Fundamentals of Pattern Recognition and Machine Learning
Free Shipping+Easy returns
Product Details
Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
Free Shipping+Easy returns
Product Details
Analysis Patterns: Reusable Object Models
Free Shipping+Easy returns
Product Details
High-Dimensional Data Analysis with Low-Dimensional
Models: Principles, Computation, and Applications
Free Shipping+Easy returns
Product Details
Advances in Machine Learning for Big Data Analysis (Intelligent Systems Reference Library, 218)
Free Shipping+Easy returns
Product Details
Ace the Data Science Interview: 201 Real Interview Questions Asked By FAANG, Tech Startups, & Wall Street
Free Shipping+Easy returns
Product Details
Data Analysis: A Model Comparison Approach To Regression, ANOVA, and Beyond, Third Edition
Free Shipping+Easy returns
Product Details
Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps
Free Shipping+Easy returns
Research
Qualitative Study Qualitative study is about formulation of concepts that explains a social phenomenon in its settings, giving due importance to the experience and views of the participants. It is a study on subjectivity to identify or explain a happening. In order to do a genuine research that results in a proper study, the researcher+ Read More
AI – Tools
Exploratory Data Analysis (EDA) is a type of storytelling for statisticians. In this post, we show you how to conduct EDA using Python and Pandas.
Data Science Blog
Welcome to episode 23 of Data Viz Today. How can visualizing streaks in your data help you find patterns and gain perspective? Host Alli Torban dives into specific ways you can see your data in a new way by highlighting the period of time that something is happening – a streak! Fea
Entrepreneur \u0026 Startups
Big data analytics examines large amounts of data to uncover hidden patterns, correlations and other insights. MATLAB has the tool Neural Network Toolbox (Deep Learning Toolbox from version 18) that provides algorithms, functions, and apps to create, train, visualize, and simulate neural networks. You can perform classification, regression, clustering, dimensionality reduction, time-series forecasting, and dynamic system modeling and control.The toolbox includes convolutional neural network and autoencoder deep learning algorithms for image classification and feature learning tasks. To speed up training of large data sets, you can distribute computations and data across multicore processors, GPUs, and computer clusters using Big Data tools (Parallel Computing Toolbox). Unsupervised learning algorithms, including self-organizing maps and competitive layers-Apps for data-fitting, pattern recognition, and clustering-Preprocessing, postprocessing, and network visualization for improving training efficiency and assessing network performance. This book develops cluster analysis and pattern recognition
AAA DATA VISUALIZATION
Graphing and Data Analysis in first grade can seem daunting but it is actually a really fun math concept because it is so visual. Kids \
Data Analysis | Data Visualization | Big Data
Dynamic expression data, nowadays obtained using high-throughput RNA sequencing, are essential to monitor transient gene expression changes and to study the dynamics of their transcriptional activity in the cell or response to stimuli. Several methods for data selection, clustering and functional analysis are available; however, these steps are usually performed independently, without exploiting and integrating