Machine learning
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The concept Machine learning represents the subject, aboutness, idea or notion of resources found in University of Missouri Libraries.
The Resource
Machine learning
Resource Information
The concept Machine learning represents the subject, aboutness, idea or notion of resources found in University of Missouri Libraries.
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- Machine learning
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- http://id.worldcat.org/fast/01004795
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- fast
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- 17th IEEE International Conference on Machine Learning and Applications : ICMLA 2018 : proceedings : 17-20 December 2018, Orlando, Florida, USA
- 1st Workshop on Energy Efficient Machine Learning and Cognitive Computing for Embedded Applications : EMC2 2018 : 25 March 2018, Williamsburg, Virginia, USA
- 2002 International Conference on Machine Learning and Cybernetics : proceedings : November 4-5, 2002, Prime Hotel, Beijing, China
- 2003 International Conference on Machine Learning and Cybernetics : proceedings : November 2-5, 2003, Sheraton Hotel, Xi'an, China
- 2007 IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning : Honolulu, HI, 1-5 April 2007
- 2008 6th International Symposium on Applied Machine Intelligence and Informatics
- 2009 7th International Symposium on Applied Machine Intelligence and Informatics
- 2009 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning : (ADPLR 2009) [i.e. ADPRL] proceedings : March 30-April 2, 2009, Sheraton Music City Hotel, Nashville, TN, USA
- 2009 IEEE Workshop on Evolving and Self-Developing Intelligent Systems (ESDIS 2009) proceedings : March 30-April 2, 2009, Sheraton Music City Hotel, Nashville, TN, USA
- 2011 IEEE International Workshop on Machine Learning for Signal Processing
- 2012 3rd International Workshop on Cognitive Information Processing (CIP) : Baiona, Spain, May 28th -30th, 2012
- 2012 IEEE International Workshop on Machine Learning for Signal Processing : proceedings of MLSP2012 : September 23-26, Santander, Spain
- 2013 IEEE International Workshop on Machine Learning for Signal Processing : September 22-25, Southampton, United Kingdom : proceedings of MLSP2013
- 2013 International Conference on Machine Learning and Cybernetics (ICMLC)
- 2014 IEEE International Workshop on Machine Learning for Signal Processing : proceedings of MLSP2014 : September 21-24, Reims, France
- 2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL)
- 2014 IEEE Symposium on Evolving and Autonomous Learning Systems (EALS)
- 2015 IEEE International Conference on Knowledge and Systems Engineering : proceedings : 8-10 October, Ho Chi Minh City, Vietnam
- 2015 IEEE International Workshop on Machine Learning for Signal Processing : proceedings of MLSP2015 : September 17-20, Boston, USA
- 2015 International Conference on Machine Learning and Cybernetics (ICMLC)
- 2016 13th International Joint Conference on Computer Science and Software Engineering (JCSSE) : 13-15 July 2016
- 2016 15th IEEE International Conference on Machine Learning and Applications : proceedings : 18-20 December 2016, Anaheim, California
- 2016 Eighth International Conference on Knowledge and Systems Engineering (KSE) : proceedings : October 6-8, 2016, Hanoi, Vietnam
- 2016 First International Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE) : proceedings : July 6-8, 2016, Aalborg University, Aalborg, Denmark
- 2016 IEEE Information Theory Workshop (ITW)
- 2016 IEEE International Conference on Information and Automation (ICIA) : 1-3 Aug. 2016
- 2016 World Automation Congress (WAC) : July 31-August 4th, 2016, Wyndham Grand Rio Mar Beach Resort & Spa, Rio Grande, Puerto Rico
- 2016 World Automation Congress (WAC) : July 31-August 4th, 2016, Wyndham Grand Rio Mar Beach Resort & Spa, Rio Grande, Puerto Rico : congress theme: Machine Learning, Autonomous Vehicle Modeling and Control : additional theme: Cloud Computing and Cloud-Based Automation and Big Data Analytic
- 2017 17th IEEE International Conference on Computer and Information Technology : proceedings : CIT 2017 ; IEEE International Workshop on Secure and Resource-Efficient Edge Computing 2017 : SecureEdge 2017 ; IEEE International Symposium on Recent Advances of Computer and Information Technologies 2017 : RACIT 2017 : 21-23 August 2017, Helsinki, Finland
- 2017 IEEE Workshop on Data Systems for Interactive Analysis (DSIA) : 1-2 Oct. 2017
- 2018 10th International Conference on Intelligent Human-Machine Systems and Cybernetics : IHMSC 2018 : proceedings : Hangzhou, China 25-26 August 2018
- 2018 IEEE International Workshop on Machine Learning Techniques for Software Quality Evaluation (MaLTeSQuE) : proceedings : March 20, 2018, Campobasso, Italy
- 2018 International Symposium on Advanced Intelligent Informatics (SAIN) : "Revolutionize Intelligent Informatics Spectrum for Humanity" : proceeding : August 29 - 30, 2018, Yogyakarta, Indonesia
- 2018 International Symposium on Electronics and Smart Devices (ISESD) : October 23-24, 2018, Bandung, Indonesia
- 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics : IHMSC 2019 : Hangzhou, China, 24-25 August 2019
- 2019 International Conference on Applied Machine Learning : ICAML 2019 : proceedings : 27-28 September 2019, Bhubaneswar, India
- 2019 International Conference on Control, Automation and Diagnosis (ICCAD) : proceedings : 2-4 July 2019, Grenoble, France
- 2019 International Conference on Machine Learning, Big Data and Business Intelligence : MLBDBI 2019 : proceedings : 8-10 November 2019, Taiyuan, China
- 26th IEEE International Symposium on Field-Programmable Custom Computing Machines : FCCM 2018 : proceedings : 29 April-1 May 2018, Boulder, Colorado, USA
- 27th IEEE International Symposium on Field-Programmable Custom Computing Machines : proceedings : 28 April-1 May 2019, San Diego, California
- 3D neural network visualization with TensorSpace
- 3D shape analysis : fundamentals, theory, and applications
- 5 questions on artificial intelligence
- 5 questions on artificial intelligence
- 5th International Conference on Machine Learning and Applications : ICMLA 2006 : proceedings : 14-16 December 2006, Orlando, Florida
- 6 Trends Framing the State of AI and ML
- ADCOM 2016 : 22nd International Conference on Advanced Computing and Communications : proceedings : 8-10 September 2016, Bangalore, India
- AI and deep learning for NLP : tools and techniques for the enterprise
- AI and machine learning for healthcare : an overview of tools and challenges for building a health-tech data pipeline
- AI for finance
- AI for marketing and product innovation : powerful new tools for predicting trends, connecting with customers, and closing sales
- Abstract state machines, Alloy, B and Z : Second International Conference, ABZ 2010, Orford, QC, Canada, February 22-25, 2010 ; proceedings
- Abstract state machines, Alloy, B, TLA, VDM, and Z : 4th International Conference, ABZ 2014, Toulouse, France, June 2-6, 2014. Proceedings
- Abstract state machines, Alloy, B, VDM, and Z : third International Conference, ABZ 2012, Pisa, Italy, June 18-21, 2012. Proceedings
- Accelerate deep learning on Raspberry Pi
- Achieving real business outcomes from artificial intelligence : enterprise considerations for AI initiatives
- Active conceptual modeling of learning : next generation learning-base system development
- Adaption and learning in multi-agent systems : IJCAI '95 workshop, Montréal, Canada, August 21, 1995, proceedings
- Adaptive and learning agents : Second Workshop, ALA 2009, Held as Part of the AAMAS 2009 Conference in Budapest, Hungary, May 12, 2009. Revised Selected Papers
- Adaptive and learning agents : international workshop, ALA 2011, held at AAMAS 2011, Taipei, Taiwan, May 2, 2011, Revised selected papers
- Adaptive and natural computing algorithms : 8th international conference, ICANNGA 2007, Warsaw, Poland, April 11-14, 2007 : proceedings
- Adaptive and natural computing algorithms : proceedings of the international conference in Coimbra, Portugal, 2005
- Advanced NLP projects with TensorFlow 2.0
- Advanced R statistical programming and data models : analysis, machine learning, and visualization
- Advanced applied deep learning : convolutional neural networks and object detection
- Advanced computer vision with TensorFlow
- Advanced data analytics using Python : with machine learning, deep learning and NLP examples
- Advanced deep learning with Keras
- Advanced deep learning with Keras : apply deep learning techniques, autoencoders, GANs, variational autoencoders, deep reinforcement learning, policy gradients, and more
- Advanced deep learning with Python
- Advanced deep learning with R : become an expert at designing, building, and improving advanced neural network models using R
- Advanced lectures on machine learning : ML Summer Schools 2003, Canberra, Australia, February 2-14, 2003, Tübingen, Germany, August 4-16, 2003 : revised lectures
- Advanced lectures on machine learning : Machine Learning Summer School 2002, Canberra, Australia, February 11-22, 2002 : revised lectures
- Advanced machine learning
- Advanced machine learning technologies and applications : first international conference, AMLTA 2012, Cairo, Egypt, December 8-10, 2012, proceedings
- Advanced machine learning technologies and applications : second International Conference, AMLTA 2014, Cairo, Egypt, November 28-30, 2014. Proceedings
- Advanced machine learning with Python : solve challenging data science problems by mastering cutting-edge machine learning techniques in Python
- Advanced machine learning with scikit-learn : tools and techniques for predictive analytics in Python
- Advanced statistics and data mining for data science
- Advanced structured prediction
- Advances in Artificial Intelligence : 14th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, AI 2001 Ottawa, Canada, June 79, 2001 Proceedings
- Advances in artificial intelligence : 12th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, AI'98 Vancouver, BC, Canada, June 18-20, 1998 : proceedings
- Advances in computation and intelligence : 4th International Symposium on Intelligence Computation and Applications, ISICA 2009, Huangshi, China, October 23-25, 2009 : proceedings
- Advances in computation and intelligence : 5th international symposium, ISICA 2010, Wuhan, China, October 22-24, 2010 : proceedings
- Advances in computation and intelligence : second international symposium, ISICA 2007, Wuhan, China, September 21-23, 2007 : proceedings
- Advances in computation and intelligence : third international symposium, ISICA 2008, Wuhan, China, December 19-21, 2008 ; proceedings
- Advances in financial machine learning
- Advances in financial machine learning
- Advances in learning classifier systems : 4th international workshop, IWLCS 2001, San Francisco, CA, USA, July 7-8, 2001 : revised papers
- Advances in learning classifier systems : third international workshop, IWLCS 2000, Paris, France, September 15-16, 2000 : revised papers
- Advances in machine learning : first Asian Conference on Machine Learning, ACML 2009, Nanjing, China, November 2-4, 2009 : proceedings
- Advances in machine learning and cybernetics : 4th international conference, ICMLC 2005, Guangzhou, China, August 18-21, 2005 : revised selected papers
- Agile machine learning : effective machine learning inspired by the agile manifesto
- Algorithmic Learning Theory : 14th International Conference, ALT 2003, Sapporo, Japan, October 17-19, 2003 : proceedings
- Algorithmic learning theory : 10th International Conference, ALT'99, Tokyo, Japan, December 6-8, 1999 : proceedings
- Algorithmic learning theory : 11th international conference, ALT 2000 Sydney, Australia, December 11-13, 2000, proceedings
- Algorithmic learning theory : 12th International Conference, ALT 2001, Washington, DC, USA, November 25-28, 2001 : proceedings
- Algorithmic learning theory : 15th international conference, ALT 2004, Padova, Italy, October 2-5, 2004 : proceedings
- Algorithmic learning theory : 16th international conference, ALT 2005, Singapore, October 8-11, 2005 : proceedings
- Algorithmic learning theory : 17th international conference ALT 2006 : Barcelona, Spain, October 2006 : proceedings
- Algorithmic learning theory : 18th international conference, ALT 2007, Sendai, Japan, October 1-4, 2007 : proceedings
- Algorithmic learning theory : 19th international conference, ALT 2008, Budapest, Hungary, October 13-16, 2008 : proceedings
- Algorithmic learning theory : 20th International Conference, ALT 2009, Porto, Portugal, October 3-5, 2009 : proceedings
- Algorithmic learning theory : 21st International Conference, ALT 2010, Canberra, Australia, October 6-8, 2010, proceedings
- Algorithmic learning theory : 22nd international conference, ALT 2011, Espoo, Finland, October 5-7, 2011 : proceedings
- Algorithmic learning theory : 23rd International Conference, ALT 2012, Lyon, France, October 29-31, 2012. Proceedings
- Algorithmic learning theory : 24th International Conference, ALT 2013, Singapore, October 6-9, 2013. Proceedings
- Algorithmic learning theory : 6th international workshop, ALT '95, Fukuoka, Japan, October 18-20, 1995 : proceedings
- Algorithmic learning theory : 9th international conference, ALT '98, Otzenhausen, Germany, October 8-10, 1998 : proceedings
- Algorithmic probability and friends : Bayesian prediction and artificial intelligence : Papers from the Ray Solomonoff 85th Memorial Conference, Melbourne, VIC, Australia, November 30-December 2, 2011
- Amazon machine learning
- An introduction to machine learning interpretability : an applied perspective on fairness, accountability, transparency, and explainable AI
- An introduction to machine learning models in production : how to transition from one-off models to reproducible pipelines
- Analyzing and visualizing data with F#
- Anticipatory behavior in adaptive learning systems : from brains to individual and social behavior
- Anticipatory behavior in adaptive learning systems : from psychological theories to artificial cognitive systems
- Apache Spark 2 data processing and real-time analytics : master complex big data processing, stream analytics, and machine learning with Apache
- Apache Spark 2.x machine learning cookbook : over 100 recipes to simplify machine learning model implementations with Spark
- Apache Spark deep learning cookbook : over 80 recipes that streamline deep learning in a distributed environment with Apache Spark
- Apache Spark machine learning blueprints : develop a range of cutting-edge machine learning projects with Apache Spark using this actionable guide
- Apache Spark quick start guide : quickly learn the art of writing efficient big data applications with Apache Spark
- Applications of embeddings and deep learning at Groupon
- Applied analytics through case studies using SAS and R : implementing predictive models and machine learning techniques
- Applied data science with Python and Jupyter
- Applied deep learning : a case-based approach to understanding neural networks
- Applied deep learning and computer vision for self-driving cars : build autonomous vehicles using deep neural networks and behavior-cloning techniques
- Applied machine learning and deep learning with R
- Applied machine learning for healthcare
- Applied machine learning with R
- Applied natural language processing with Python : implementing machine learning and deep learning algorithms for natural language processing
- Applied text analysis with Python : enabling language-aware data products with machine learning
- Applied unsupervised learning with Python : discover hidden patterns and relationships in unstructured data with Python
- Applied unsupervised learning with R
- Artificial Intelligence By Example - Second Edition
- Artificial Intelligence Conference 2019 : New York, New York
- Artificial intelligence : the simplest way
- Artificial intelligence and machine learning fundamentals
- Artificial intelligence and machine learning fundamentals
- Artificial intelligence and machine learning in industry : perspectives from leading practitioners
- Artificial intelligence basics : a non-technical introduction
- Artificial intelligence in 3 hours
- Artificial intelligence now : current perspectives from O'Reilly Media
- Artificial intelligence on human behavior : new insights into customer segmentation
- Artificial neural networks and machine learning-- ICANN 2011 : 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part II
- Artificial neural networks and machine learning-- ICANN 2011 : 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, proceedings, Part I
- Artificial neural networks and machine learning-- ICANN 2012 : 22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, September 11-14, 2012, Proceedings, Part II
- Automating DevOps for machine learning
- Autonomous cars : deep learning and computer vision in Python
- Autonomous learning systems : from data streams to knowledge in real-time
- Avoiding the pitfalls of deep learning : solving model overfitting with regularization and dropout
- Azure cognitive services for developers
- Azure masterclass : manage Azure cloud with ARM templates
- Basic data analysis with Java
- Beginning AI bot frameworks : getting started with bot development
- Beginning MATLAB and Simulink : from novice to professional
- Beginning application development with TensorFlow and Keras
- Beginning application development with TensorFlow and Keras : learn to design, develop, train, and deploy TensorFlow and Keras models as real-world applications
- Beginning artificial intelligence with the Raspberry Pi
- Beginning data science with Python and Jupyter
- Beginning machine learning in iOS : CoreML framework
- Beginning machine learning with AWS
- Best practices for bringing AI to the enterprise
- Big data analytics for intelligent healthcare management
- Big data analytics using Apache Spark
- Big data and machine learning in quantitative investment
- Biomimetic neural learning for intelligent robots : intelligent systems, cognitive robotics, and neuroscience
- Bringing data to life : combining machine learning and art to tell a data story
- Build more inclusive TensorFlow pipelines with fairness indicators
- Building Cognitive Applications with IBM Watson Services : Volume 2 Conversation
- Building Recommender systems with machine learning and AI
- Building a big data analytics stack
- Building a recommendation engine with Scala : learn to use Scala to build a recommendation engine from scratch and empower your website users
- Building a recommendation system with R : learn the art of building robust and powerful recommendation engines using R
- Building advanced OpenCV 3 projects with Python
- Building computer vision applications using artificial neural networks : with step-by-step Eeamples in OpenCV and TensorFlow with Python
- Building enterprise data products
- Building intelligent cloud applications : develop scalable models using serverless architectures with Azure
- Building machine learning and deep learning models on Google Cloud Platform : a comprehensive guide for beginners
- Building machine learning powered applications : going from idea to product
- Building machine learning projects with TensorFlow : engaging projects that will teach you how complex data can be exploited to gain the most insight
- Building machine learning systems with Python : explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow
- Building machine learning systems with TensorFlow
- Business data science : combining machine learning and economics to optimize, automate, and accelerate business decisions
- C# machine learning projects : nine real-world projects to build robust and high-performing machine learning models with C#
- CIC 2006 : 15th International Conference on Computing : proceedings : 21-24 November, 2006, Mexico City, Mexico
- Can data science help us find what makes a hit television show
- Challenges and applications for implementing machine learning in computer vision
- Classification and learning using genetic algorithms : applications in bioinformatics and web intelligence
- Clojure for data science : statistics, big data, and machine learning for Clojure programmers
- Clustering & classification with machine learning in R : harness the power of machine learning for unsupervised & supervised learning in R
- Clustering and unsupervised learning, Part 4, Introduction to real-world machine learning
- Cognitive Information Processing (CIP), 2010 2nd International Workshop on : date, 14-16 June 2010
- Cognitive computing recipes : artificial intelligence solutions using Microsoft cognitive services and Tensorflow
- Cognitive computing with IBM Watson : build smart applications using artificial intelligence as a service
- Colloquium on "Machine Learning" : on Thursday, 28 June 1990
- Computational intelligence in business analytics : concepts, methods, and tools for big data applications
- Computational trust models and machine learning
- Computational visual media : First International Conference, CVM 2012, Beijing, China, November 8-10, 2012 : proceedings
- Computer vision and machine learning with RGB-D sensors
- Computer vision projects with OpenCV and Python 3 : six end-to-end projects build using machine learning with OpenCV, Python, and TensorFlow
- Conformal prediction for reliable machine learning : theory, adaptations and applications
- Conformal prediction for reliable machine learning : theory, adaptations, and applications
- Considering TensorFlow for the enterprise : an overview of the deep learning ecosystem
- Convex optimization : algorithms and complexity
- Cost-sensitive machine learning
- Customizing state-of-the-art deep learning models for new computer vision solutions
- Dan Van boxel's deep learning with TensorFlow
- Data Mining and Machine Learning in Cybersecurity
- Data Science Programming All-In-One for Dummies
- Data analysis with Python : a modern approach
- Data analysis, machine learning and applications : proceedings of the 31st Annual Conference of the Gesellschaft für̈ Klassifikation e.V., Albert-Ludwigs-Universität Freiburg, March 7-9, 2007
- Data analysis, machine learning and knowledge discovery
- Data analytics and machine learning fundamentals : LiveLessons
- Data and social good : using data science to improve lives, fight injustice, and support democracy
- Data science algorithms in a week : data analysis, machine learning, and more
- Data science algorithms in a week : top 7 algorithms for scientific computing, data analysis, and machine learning
- Data science and engineering at enterprise scale : notebook-driven results and analysis
- Data science and machine learning with Python - hands on!
- Data science and machine learning with Python--Hands on!
- Data science fundamentals, Part 1, Learning basic concepts, data wrangling, and databases with Python
- Data science fundamentals, Part 2, Machine learning and statistical analysis
- Data science in the cloud with Microsoft Azure machine learning and Python
- Data science in the cloud with Microsoft Azure machine learning and R : 2015 update
- Data science projects with Python : a case study approach to successful data science projects using Python, pandas, and scikcit-learn
- Data science with Microsoft Azure and R
- Data science with Python : combine Python with machine learning principles to discover hidden patterns in raw data
- Data statistics with full stack Python
- Data visualization recipes in Python
- Dealing with real-world data, Part 1, Introduction to real-world machine learning
- Deep Learning - Grundlagen und Implementierung : Neuronale Netze mit Python und PyTorch programmieren
- Deep Learning for Natural Language Processing : Solve Your Natural Language Processing Problems with Smart Deep Neural Networks
- Deep Learning for the Life Sciences : Applying Deep Learning to Genomics, Microscopy, Drug Discovery, and More
- Deep Learning für die Biowissenschaften : Einsatz von Deep Learning in Genomik, Biophysik, Mikroskopie und medizinischer Analyse
- Deep Learning mit Python und Keras : Das Praxis-Handbuch vom Entwickler der Keras-Bibliothek
- Deep Learning with TensorFlow
- Deep Learning with TensorFlow : Explore neural networks and build intelligent systems with Python, 2nd Edition
- Deep learning
- Deep learning
- Deep learning : a practitioner's approach
- Deep learning : das umfassende Handbuch : Grundlagen, aktuelle Verfahren und Algorithmen, neue Forschungsansätze
- Deep learning : moving toward artificial intelligence with neural networks and machine learning
- Deep learning : practical neural networks with Java : build and run intelligent applications by leveraging key Java machine learning libraries : a course in three modules
- Deep learning Kochbuch : Praxisrezepte für einen schnellen Einstieg
- Deep learning and neural networks using Python - Keras : the complete beginners guide
- Deep learning and the game of Go
- Deep learning architecture for building artificial neural networks
- Deep learning by example : a hands-on guide to implementing advanced machine learning algorithms and neural networks
- Deep learning cookbook : practical recipes to get started quickly
- Deep learning crash course
- Deep learning for coders with fastai and PyTorch : AI applications without a PhD
- Deep learning for computer vision with SAS : an introduction
- Deep learning for dummies
- Deep learning for natural language processing : applications of deep neural networks to machine learning tasks
- Deep learning for natural language processing : creating neural networks with Python
- Deep learning for numerical applications with SAS
- Deep learning for recommender systems, or How to compare pears with apples
- Deep learning for search
- Deep learning for strategic decision makers : understanding deep learning and how it produces business value
- Deep learning for time series data
- Deep learning from scratch : building with Python from first principles
- Deep learning illustrated : a visual, interactive guide to artificial intelligence
- Deep learning mit R und Keras : Das Praxis-Handbuch : von Entwicklern von Keras und RStudio
- Deep learning pipeline : building a deep learning model with TensorFlow
- Deep learning receptury
- Deep learning techniques for biomedical and health informatics
- Deep learning through sparse and low-rank modeling
- Deep learning using OpenPose : learn Pose estimation models and build 5 AI apps
- Deep learning with Apache Spark
- Deep learning with Keras : implement neural networks with Keras on Theano and TensorFlow
- Deep learning with Microsoft Cognitive Toolkit quick start guide : a practical guide to building neural networks using Microsoft's open source deep learning framework
- Deep learning with PyTorch
- Deep learning with PyTorch : a practical approach to building neural network models using PyTorch
- Deep learning with PyTorch quick start guide : learn to train and deploy neural network models in Python
- Deep learning with Python
- Deep learning with Python
- Deep learning with Python : a hands-on introduction
- Deep learning with Python video edition
- Deep learning with R
- Deep learning with R cookbook : over 45 unique recipes to delve into neural network techniques using R 3.5x
- Deep learning with R for beginners : design neural network models in R 3.5 using TensorFlow, Keras, and MXNet
- Deep learning with R in motion
- Deep learning with TensorFlow
- Deep learning with TensorFlow
- Deep learning with TensorFlow 2 and Keras : regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API
- Deep learning with TensorFlow : take your machine learning knowledge to the next level with the power of TensorFlow
- Deep learning with applications using Python : chatbots and face, object, and speech recognition with TensorFlow and Keras
- Deep reinforcement learning and GANS Livelessons
- Deep reinforcement learning hands-on : apply modern RL methods to practical problems of chatbots, robotics, discrete optimization, web automation, and more
- Deep reinforcement learning hands-on : apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more
- Deep-ML 2019 : 2019 International Conference on Deep Learning and Machine Learning in Emerging Applications : proceedings : 26-28 August 2019, Istanbul, Turkey
- Demand-driven associative classification
- Deploying Spark ML pipelines in production on AWS : how to publish pipeline artifacts and run pipelines in production
- Deploying machine learning models as microservices using Docker : a REST-based architecture for serving ML model outputs at scale
- Deterministic and statistical methods in machine learning : first international workshop, Sheffield, UK, September 7-10, 2004 : revised lectures
- Developing a computer coding scheme for the implicit achievement motive
- Developing an image classifier using TensorFlow : convolutional neural networks
- Discovery science : 15th International Conference, DS 2012, Lyon, France, October 29-31, 2012 : proceedings
- Discovery science : 16th International Conference, DS 2013, Singapore, October 6-9, 2013, Proceedings
- Discovery science : 17th International Conference, DS 2014, Bled, Slovenia, October 8-10, 2014. Proceedings
- Distributed deep learning with Apache Spark
- Dynamic neural network programming with PyTorch
- END-TO-END DATA SCIENCE WITH SAS : a hands-on programming guide;a hands-on programming guide
- Effective Amazon Machine Learning
- Effective Amazon machine learning : machine learning in the Cloud
- Effective enterprise architecture
- Efficient learning machines : theories, concepts, and applications for engineers and system Designers