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342392047625U T T A R P R A D E S H00U T T A R P R A D E S H COURSE CURRICULUMLTP/SSW/FWNo. of PSDATOTAL CREDIT UNITS300234Course Title: Deep & Reinforcement Learning Credit Units: 04Course Level: PG Course Code: NewCourse Description: Deep learning is a form of machine learning that enables machines to learn from experience. Artificial Intelligence is the most disruptive technology of our times, and Deep Learning is the neural (human brain simile) behind AI systems. The focus of Deep and Reinforcement learning DRL will be to teach how to attain a complex objective (goal) or maximize along a particular dimension over many steps for example, maximize the points won in a game over many moves. Reinforcement learning algorithms can be expected to perform better and better in more ambiguous, real-life environments while choosing from an arbitrary number of possible actions, rather than from the limited options like in a simple video game. Course Objectives: To understand fundamentals of Deep and Reinforcement Learning. To apply various tools and techniques.To apply the knowledge in solving business problems Pre-requisites: NoneCourse Contents/Syllabus:Weightage (%)Module 1: Neural Network /Deep Learning 15%Introduction to Deep Learning , What problems can deep learning solveElements of RL, Limitations and ScopePrinciples of Deep Learning :RNN/LSTM/GRU, Convolutional Neural Networks, Transfer Learning A Concise History of Neural Networks and Deep Learning Case study (CNN) Module 2: Natural Language Processing 20%Overview of NLP & application Text Mining, Generation Case study on Generation procedures Module 3: Predictive Analytics25%Predictive Analytics : Meaning, Scope, ImportanceLogistic Regression, Time Series (ARIMA) Case study on Time series forecasting Ensemble Techniques: Bagging, BootstrappingModule 4: Reinforcement Learning25%What is Reinforcement Learning, Elements of RL, Limitations and ScopeMarkov Decision , Markov Decision Process (MDP)Monte Carlo Prediction Basics of OpenAI ,Keras, TensorFlowChallenges, and opportunities of deep learning and Reinforcement Learning from a business perspective, Case-study : dynamic pricing Module 5: Opportunities, Perspectives and Applications15%Business Impact of?Deep Learning TechnologyMan v/s Machines, Google DeepMind, AlphaGo Applications of DRL in Games, Finance, Robotics and HealthCareNew Research and?Future DirectionsStudent Learning Outcomes:On completion of the course the student will be able to:?To categorize the business problems that can be solved by Deep & Reinforcement Learning (DRL)To debate on the business applications of Natural Language Processing To apply DRL tools and techniques in select business situations.Pedagogy for Course Delivery:The course pedagogy will include lectures, numerical practice, case studies. It also includes discussion on problems and challenges faced by managers.List of Professional Skill Development Activities (PSDA):Complete Amity University Online (AUO) videos, module Quizzes Complete Amity University Online (AUO) Short Assignment /project (as announced by them)Submit a Deep and Reinforcement Learning group project. Topics not limited to what is given belowText MiningPredictive AnalyticsGamingDynamic PricingKeras / TensorFlow/ OpenAI GymAssessment/ Examination Scheme:Theory L/T (%)Lab/Practical/Studio (%)1000Theory Assessment (L&T):Continuous Assessment/Internal Assessment (40 %)End Term Examination(60%)Components (Drop down)CTPSDA1PSDA2PSDA3CVAEELinkage of PSDA with Internal Assessment Component, if anyWeightage (%)10510105560Lab/ Practical/ Studio Assessment:Continuous Assessment/Internal Assessment(____ %)End Term Examination(____ %)Components (Drop downWeightage (%)Text & References: Deep Learning: A Practitioner’s Approach. Josh Patterson and Adam Gibson. O’Reilly2017Reinforcement Learning : With Open AI, TensorFlow and Keras Using PythonAbhishek Nandy,?Manisha Biswas 2018Artificial Intelligence for Business: What You Need to Know about Machine Learning and Neural Networks, Doug Rose, 2018, Introduction to Deep Learning Business Applications for Developers From Conversational Bots in Customer Service to Medical Image Processing. Armando Vieira Bernardete Ribeiro . Apress. 2018Artificial Intelligence and Machine Learning for Business A No-Nonsense Guide to Data Driven Technologies Third Edition . Steven Finlay. Relativistic. 2018Machine Learning for Absolute Beginners, Oliver Theobald . Deep Learning for Computer Vision with Python Starter Bundle. Adrian Rosebrock 1st Edition, 2017Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies, John D. Kelleher,?Brian Mac Namee,?Aoife D'Arcy2015Deep learning: adaptive computation and machine learning, Bengio,? HYPERLINK "" \o "Find all the author's book" Yoshua,? HYPERLINK "" \o "Find all the author's book" Courville,?Aaron,? HYPERLINK "" \o "Find all the author's book" Goodfellow,?Ian JReferences Dataset URL: ................
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