• Data Structures and Algorithms for Big Databases
• Data Warehousing Using the Wal-Mart Model
• Effective SQL: 61 Specific Ways to Write Better SQL
• Head First Data Analysis
• Mathematical Models for Remote Sensing Image Processing Models and Methods for the Analysis of 2D Satellite and Aerial Images
• Monetizing Machine Learning: Quickly Turn Python ML Ideas into Web Applications on the Serverless Cloud
• Time Series Data Analysis Using EViews
• Machine Learning Models and Algorithms for Big Data Classification
• Agile Data Science 2.0: Building Full-Stack Data Analytics Applications with Spark
• AI in Marketing, Sales and Service: How Marketers without a Data Science Degree can use AI, Big Data and Bots
• Applied Biostatistical Principles and Concepts
• Bayesian Data Analysis
• Big Data: A Business and Legal Guide
• Big Data: Using Smart Big Data, Analytics and Metrics to Make Better Decisions and Improve Performance
• Big Data Demystified: How to Use Big Data, Data Science and AI to Make Better Business Decisions and Gain Competitive Advantage
• Big Data, Mining, and Analytics Components of Strategic Decision Making
• Big-Data Analytics and Cloud Computing
• Community and Quality of Life. Data Needs for Informed Decision Making
• Data Analysis and Approximate Models: Model Choice, Location-Scale, Analysis of Variance, Nonparametric Regression and Image Analysis
• Data Analysis: A Model Comparison Approach to Regression, ANOVA, and Beyond
• Data Analytics in Football
• Data Analytics with Hadoop: An Introduction for Data Scientists
• Data Analytics Models and Algorithms for Intelligent Data Analysis
• Data Mining for Business Analytics: Concepts, Techniques and Applications in R
• Data Model Patterns: A Metadata Map
• Data Model Scorecard: Applying the Industry Standard on Data Model Quality
• Data Modeling Essentials
• Data Modeling for MongoDB: Building Well-Designed and Supportable MongoDB Databases
• Data Modeling Techniques for Data Warehousing
• Data Science Algorithms in a Week
• Data Science For Dummies
• Data Science from Scratch
• Data Structures And Algorithms Made Easy
• Data Communication and Computer Network Tutorial
• Data Structures and Problem Solving Using Java
• Database Design for Smarties: Using UML for Data Modeling
• Database Modeling and Design: Logical Design
• Data-driven Modelling of Structured Populations
• Enabling Things to Talk: Designing IoT solutions with the IoT Architectural Reference Model
• Fact Oriented Modeling with FCO-IM: Capturing Business Semantics in Data Models with Fully Communication Oriented Information Modeling
• Data Mining: Concepts,Models and Techniques
• From Big Data to Big Profits: Success with Data and Analytics
• Fuzzy Modeling and Genetic Algorithms or Data Mining and Exploration
• Hadoop: Data Processing and Modelling
• Healthcare Analytics: From Data to Knowledge to Healthcare Improvement
• Introduction to Machine Learning
• Learn Keras for Deep Neural Networks: A Fast-Track Approach to Modern Deep Learning with Python
• Mastering TensorFlow 1.x
• Natural Language Processing Recipes: Unlocking Text Data with Machine Learning and Deep Learning using Python
• NoSQL and SQL Data Modeling: Bringing Together Data, Semantics, and Software
• Object-Role Modeling Workbook: Data Modeling Exercises using ORM and NORMA
• Practical Computer Vision Applications Using Deep Learning with CNNs: With Detailed Examples in Python Using TensorFlow and Kivy
• Practical Statistics for Data Scientists: 50 Essential Concepts
• Predictive Analytics
• Principles of Data Structures Using C and C++
• Quantitative Trading: Algorithms, Analytics, Data, Models, Optimization
• Regression Models for Data Science in R
• Regression: Models, Methods and Applications
• Scala for Machine Learning
• Sports Analytics and Data Science: Winning the Game with Methods and Models
• Statistical and Machine-Learning Data Mining
• Sams Teach Yourself Data Structures and Algorithms in 24 Hours
• The Art of Data Science: A Guide for Anyone Who Works with Data
• The Data Industry: The Business and Economics of Information and Big Data
• The Data Model Resource Book
• The Digital Transformation Playbook: Rethink Your Business for the Digital Age
• The Enterprise Big Data Lake: Delivering the Promise of Big Data and Data Science
• The Essentials of Data Science: Knowledge Discovery Using R
• The Functional Approach to Data Management
• The Model Thinker: What You Need to Know to Make Data Work for You
• Think Like a Data Scientist: Tackle the data science process step-by-step
• What to Do When Machines Do Everything: How to Get Ahead in a World of Ai, Algorithms, Bots, and Big Data
• 500 Data Science Interview Questions and Answers
• An Introduction to Data: Everything You Need to Know About AI, Big Data and Data Science
• Big Data: A Revolution That Will Transform How We Live, Work, and Think
• Cloud Computing: Technologies and Strategies of the Ubiquitous Data Center
• Data Driven: Harnessing Data and AI to Reinvent Customer Engagement
• Managing Data in Motion: Data Integration Best Practice Techniques and Technologies
• Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Instagram, GitHub, and More
• Practical Web Scraping for Data Science: Best Practices and Examples with Python
• Seven Databases in Seven Weeks
• The SAGE Handbook of Qualitative Data Collection
• The Sales Acceleration Formula: Using Data, Technology, and Inbound Selling to go from $0 to $100 Million
• The Little Data Book on Information and Communication Technology 2018
• Computer and Machine Vision: Theory, Algorithms, Practicalities
• How to Think About Algorithms
• Algorithms For Dummies
• Algorithms Illuminated (Part 2): Graph Algorithms and Data Structures
• grokking algorithms
• Introduction to Algorithms
• Introduction to Genetic Algorithms
• Analysis of Algorithms: An Active Learning Approach
• Machine Learning For Absolute Beginners
• Kernel Methods and Machine Learning
• Machine Learning: An Algorithmic Perspective
• The art of computer programming, volume 2: seminumerical algorithms
• Discrete and Continuous Fourier Transforms: Analysis, Applications and Fast Algorithms
• The Hundred-Page Machine Learning Book
• Algorithms for Data Science
• Master Machine Learning Algorithms: Discover How They Work and Implement Them From Scratch
• The Deep Learning Revolution
• Database Design for Mere Mortals
• Databases demystified
• Hands-on Database: An Introduction to Database Design and Development
• Data Science and Analytics for Ordinary People
• The Data Science Handbook
• Data Science for Business
• Doing Data Science
• AI for Data science
• Applied Deep Learning: A Case-Based Approach to Understanding Deep Neural Networks
• Artificial Neural Networks: A Practical Course
• Artificial Neural Networks in Real-life Applications
• Comprehensive Mathematics for Computer Scientists 2: Calculus and ODEs, Splines, Probability, Fourier andWavelet Theory, Fractals and Neural Networks, Categories and Lambda Calculus
• Computational Intelligence and Its Applications: Evolutionary Computation, Fuzzy Logic, Neural Network and Support Vector Machine Techniques
• Computer Science, Robotics, Artificial Intelligence, Neural Networks, IT, Mobiles
• Deep Learning and Convolutional Neural Networks for Medical Image Computing
• Deep Learning: Practical Neural Networks with Java
• Neural Networks and Learning Machines
• Elements of Artificial Neural Networks
• Evolutionary computation
• FPGA Implementations of Neural Networks
• Intelligent Optimisation Techniques: Genetic Algorithms, Tabu Search, Simulated Annealing and Neural Networks
• Introduction to the math of neural networks
• Neural Networks − A Visual Introduction For Beginners
• Neural Modeling and Neural Networks
• Neural Network Applications
• Neural network dynamics
• Neural Network Programming with Java
• Neural Networks and Deep Learning: A Textbook
• Neural Networks for Applied Sciences and Engineering
• Neural Networks with R
• 3D Computer Vision: Efficient Methods and Applications
• Neural-Based Orthogonal Data Fitting: The EXIN Neural Networks
• New Directions in Neural Networks
• Recent Advances of Neural Network Models and Applications
• TensorFlow in 1 Day: Make your own Neural Network
• Theory and Applications of Neural Networks
• Unsupervised Deep Learning in Python
• Arduino Computer Vision Programming
• Computer Graphics, Visualization, Computer Vision and Image Processing
• Computer and Machine Vision: Theory, Algorithms, Practicalities
• Computer Vision and Applications: A Guide for Students and Practitioners
• Computer Vision Metrics: Survey, Taxonomy and Analysis of Computer Vision, Visual Neuroscience, and Deep Learning
• Computer Vision: A Modern Approach
• Computer Vision: Models, Learning, and Inference
• Foundations of Computer Vision: Computational Geometry, Visual Image Structures and Object Shape Detection
• Handbook of Geometric Computing
• Natural Image Statistics: A Probabilistic Approach to Early Computational Vision
• Practical Computer Vision Applications Using Deep Learning with CNNs
• Raspberry Pi Robotic Projects
• Recent Developments in Computer Vision
• Robust Computer Vision: Theory and Applications
• Computer Vision: Algorithms and Applications
• Multiple View Geometry in Computer Vision
• Integration of Natural Language and Vision Processing: Computational Models and Systems
• Interactive Curve Modeling: With Applications to Computer Graphics, Vision and Image Processing
• Numerical Algorithms
• Programming Computer Vision with Python
• Computer Vision and Machine Learning with RGB-D Sensors
• Advances in Embedded Computer Vision
• Computer Vision for Visual Effects
• Knowledge Transfer between Computer Vision and Text Mining
• Explainable and Interpretable Models in Computer Vision and Machine Learning
• Concise Computer Vision: An Introduction into Theory and Algorithms
• Database System Concepts
• Databases for Small Business: Essentials of Database Management, Data Analysis, and Staff Training for Entrepreneurs and Professionals
• Database Management System Tutorial
• Distributed Database Management Systems: A Practical Approach
• Database management systems
• Advanced Data Warehouse Design
• Dark Web: Exploring and Data Mining the Dark Side of the Web
• Data Mining with Rattle and R
• Data Preparation for Data Mining
• Data-Driven Marketing: The 15 Metrics Everyone in Marketing Should Know
• Frontiers in Massive Data Analysis
• Making Sense of Data I
• Making Sense of Data II
• Mastering Data Warehouse Aggregates
• Mastering Data Warehouse Design: Relational and Dimensional Techniques
• The Data Warehouse Lifecycle Toolkit
• Building the Data Warehouse