Machine Learning And Music Generation

Download Machine Learning And Music Generation full books in PDF, epub, and Kindle. Read online Machine Learning And Music Generation ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Deep Learning Techniques for Music Generation

Author : Jean-Pierre Briot
Publisher : Springer
ISBN 13 : 3319701630
Total Pages : 284 pages
Book Rating : 4.3/5 (197 download)

DOWNLOAD NOW!

Book Synopsis Deep Learning Techniques for Music Generation by : Jean-Pierre Briot

Download or read book Deep Learning Techniques for Music Generation written by Jean-Pierre Briot and published by Springer. This book was released on 2019-11-08 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a survey and analysis of how deep learning can be used to generate musical content. The authors offer a comprehensive presentation of the foundations of deep learning techniques for music generation. They also develop a conceptual framework used to classify and analyze various types of architecture, encoding models, generation strategies, and ways to control the generation. The five dimensions of this framework are: objective (the kind of musical content to be generated, e.g., melody, accompaniment); representation (the musical elements to be considered and how to encode them, e.g., chord, silence, piano roll, one-hot encoding); architecture (the structure organizing neurons, their connexions, and the flow of their activations, e.g., feedforward, recurrent, variational autoencoder); challenge (the desired properties and issues, e.g., variability, incrementality, adaptability); and strategy (the way to model and control the process of generation, e.g., single-step feedforward, iterative feedforward, decoder feedforward, sampling). To illustrate the possible design decisions and to allow comparison and correlation analysis they analyze and classify more than 40 systems, and they discuss important open challenges such as interactivity, originality, and structure. The authors have extensive knowledge and experience in all related research, technical, performance, and business aspects. The book is suitable for students, practitioners, and researchers in the artificial intelligence, machine learning, and music creation domains. The reader does not require any prior knowledge about artificial neural networks, deep learning, or computer music. The text is fully supported with a comprehensive table of acronyms, bibliography, glossary, and index, and supplementary material is available from the authors' website.

Machine Learning and Music Generation

Author : José M. Iñesta
Publisher : Routledge
ISBN 13 : 1351234528
Total Pages : 153 pages
Book Rating : 4.3/5 (512 download)

DOWNLOAD NOW!

Book Synopsis Machine Learning and Music Generation by : José M. Iñesta

Download or read book Machine Learning and Music Generation written by José M. Iñesta and published by Routledge. This book was released on 2018-10-16 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational approaches to music composition and style imitation have engaged musicians, music scholars, and computer scientists since the early days of computing. Music generation research has generally employed one of two strategies: knowledge-based methods that model style through explicitly formalized rules, and data mining methods that apply machine learning to induce statistical models of musical style. The five chapters in this book illustrate the range of tasks and design choices in current music generation research applying machine learning techniques and highlighting recurring research issues such as training data, music representation, candidate generation, and evaluation. The contributions focus on different aspects of modeling and generating music, including melody, chord sequences, ornamentation, and dynamics. Models are induced from audio data or symbolic data. This book was originally published as a special issue of the Journal of Mathematics and Music.

Hands-On Music Generation with Magenta

Author : Alexandre DuBreuil
Publisher : Packt Publishing Ltd
ISBN 13 : 1838825762
Total Pages : 348 pages
Book Rating : 4.8/5 (388 download)

DOWNLOAD NOW!

Book Synopsis Hands-On Music Generation with Magenta by : Alexandre DuBreuil

Download or read book Hands-On Music Generation with Magenta written by Alexandre DuBreuil and published by Packt Publishing Ltd. This book was released on 2020-01-31 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design and use machine learning models for music generation using Magenta and make them interact with existing music creation tools Key FeaturesLearn how machine learning, deep learning, and reinforcement learning are used in music generationGenerate new content by manipulating the source data using Magenta utilities, and train machine learning models with itExplore various Magenta projects such as Magenta Studio, MusicVAE, and NSynthBook Description The importance of machine learning (ML) in art is growing at a rapid pace due to recent advancements in the field, and Magenta is at the forefront of this innovation. With this book, you’ll follow a hands-on approach to using ML models for music generation, learning how to integrate them into an existing music production workflow. Complete with practical examples and explanations of the theoretical background required to understand the underlying technologies, this book is the perfect starting point to begin exploring music generation. The book will help you learn how to use the models in Magenta for generating percussion sequences, monophonic and polyphonic melodies in MIDI, and instrument sounds in raw audio. Through practical examples and in-depth explanations, you’ll understand ML models such as RNNs, VAEs, and GANs. Using this knowledge, you’ll create and train your own models for advanced music generation use cases, along with preparing new datasets. Finally, you’ll get to grips with integrating Magenta with other technologies, such as digital audio workstations (DAWs), and using Magenta.js to distribute music generation apps in the browser. By the end of this book, you'll be well-versed with Magenta and have developed the skills you need to use ML models for music generation in your own style. What you will learnUse RNN models in Magenta to generate MIDI percussion, and monophonic and polyphonic sequencesUse WaveNet and GAN models to generate instrument notes in the form of raw audioEmploy Variational Autoencoder models like MusicVAE and GrooVAE to sample, interpolate, and humanize existing sequencesPrepare and create your dataset on specific styles and instrumentsTrain your network on your personal datasets and fix problems when training networksApply MIDI to synchronize Magenta with existing music production tools like DAWsWho this book is for This book is for technically inclined artists and musically inclined computer scientists. Readers who want to get hands-on with building generative music applications that use deep learning will also find this book useful. Although prior musical or technical competence is not required, basic knowledge of the Python programming language is assumed.

Generative Deep Learning

Author : David Foster
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492041890
Total Pages : 360 pages
Book Rating : 4.4/5 (92 download)

DOWNLOAD NOW!

Book Synopsis Generative Deep Learning by : David Foster

Download or read book Generative Deep Learning written by David Foster and published by "O'Reilly Media, Inc.". This book was released on 2019-06-28 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of generative deep learning models, such as variational autoencoders,generative adversarial networks (GANs), encoder-decoder models and world models. Author David Foster demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to some of the most cutting-edge algorithms in the field. Through tips and tricks, you’ll understand how to make your models learn more efficiently and become more creative. Discover how variational autoencoders can change facial expressions in photos Build practical GAN examples from scratch, including CycleGAN for style transfer and MuseGAN for music generation Create recurrent generative models for text generation and learn how to improve the models using attention Understand how generative models can help agents to accomplish tasks within a reinforcement learning setting Explore the architecture of the Transformer (BERT, GPT-2) and image generation models such as ProGAN and StyleGAN

Handbook of Artificial Intelligence for Music

Author : Eduardo Reck Miranda
Publisher : Springer Nature
ISBN 13 : 3030721167
Total Pages : 994 pages
Book Rating : 4.0/5 (37 download)

DOWNLOAD NOW!

Book Synopsis Handbook of Artificial Intelligence for Music by : Eduardo Reck Miranda

Download or read book Handbook of Artificial Intelligence for Music written by Eduardo Reck Miranda and published by Springer Nature. This book was released on 2021-07-02 with total page 994 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents comprehensive coverage of the latest advances in research into enabling machines to listen to and compose new music. It includes chapters introducing what we know about human musical intelligence and on how this knowledge can be simulated with AI. The development of interactive musical robots and emerging new approaches to AI-based musical creativity are also introduced, including brain–computer music interfaces, bio-processors and quantum computing. Artificial Intelligence (AI) technology permeates the music industry, from management systems for recording studios to recommendation systems for online commercialization of music through the Internet. Yet whereas AI for online music distribution is well advanced, this book focuses on a largely unexplored application: AI for creating the actual musical content.

Artificial Intelligence in Music, Sound, Art and Design

Author : Juan Romero
Publisher : Springer Nature
ISBN 13 : 3030729141
Total Pages : 501 pages
Book Rating : 4.0/5 (37 download)

DOWNLOAD NOW!

Book Synopsis Artificial Intelligence in Music, Sound, Art and Design by : Juan Romero

Download or read book Artificial Intelligence in Music, Sound, Art and Design written by Juan Romero and published by Springer Nature. This book was released on 2021-04-01 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th European Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2021, held as part of Evo* 2021, as Virtual Event, in April 2021, co-located with the Evo* 2021 events, EvoCOP, EvoApplications, and EuroGP. The 24 revised full papers and 7 short papers presented in this book were carefully reviewed and selected from 66 submissions. They cover a wide range of topics and application areas, including generative approaches to music and visual art, deep learning, and architecture.

Algorithmic Composition

Author : Gerhard Nierhaus
Publisher : Springer Science & Business Media
ISBN 13 : 3211755403
Total Pages : 294 pages
Book Rating : 4.2/5 (117 download)

DOWNLOAD NOW!

Book Synopsis Algorithmic Composition by : Gerhard Nierhaus

Download or read book Algorithmic Composition written by Gerhard Nierhaus and published by Springer Science & Business Media. This book was released on 2009-08-28 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithmic composition – composing by means of formalizable methods – has a century old tradition not only in occidental music history. This is the first book to provide a detailed overview of prominent procedures of algorithmic composition in a pragmatic way rather than by treating formalizable aspects in single works. In addition to an historic overview, each chapter presents a specific class of algorithm in a compositional context by providing a general introduction to its development and theoretical basis and describes different musical applications. Each chapter outlines the strengths, weaknesses and possible aesthetical implications resulting from the application of the treated approaches. Topics covered are: markov models, generative grammars, transition networks, chaos and self-similarity, genetic algorithms, cellular automata, neural networks and artificial intelligence are covered. The comprehensive bibliography makes this work ideal for the musician and the researcher alike.

Proceedings of International Conference on Computational Intelligence, Data Science and Cloud Computing

Author : Valentina Emilia Balas
Publisher : Springer Nature
ISBN 13 : 9813349689
Total Pages : 795 pages
Book Rating : 4.8/5 (133 download)

DOWNLOAD NOW!

Book Synopsis Proceedings of International Conference on Computational Intelligence, Data Science and Cloud Computing by : Valentina Emilia Balas

Download or read book Proceedings of International Conference on Computational Intelligence, Data Science and Cloud Computing written by Valentina Emilia Balas and published by Springer Nature. This book was released on 2021 with total page 795 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes selected papers presented at International Conference on Computational Intelligence, Data Science and Cloud Computing (IEM-ICDC) 2020, organized by the Department of Information Technology, Institute of Engineering & Management, Kolkata, India, during 25-27 September 2020. It presents substantial new research findings about AI and robotics, image processing and NLP, cloud computing and big data analytics as well as in cyber security, blockchain and IoT, and various allied fields. The book serves as a reference resource for researchers and practitioners in academia and industry.

AI and Machine Learning for Coders

Author : Laurence Moroney
Publisher : O'Reilly Media
ISBN 13 : 1492078166
Total Pages : 393 pages
Book Rating : 4.4/5 (92 download)

DOWNLOAD NOW!

Book Synopsis AI and Machine Learning for Coders by : Laurence Moroney

Download or read book AI and Machine Learning for Coders written by Laurence Moroney and published by O'Reilly Media. This book was released on 2020-10-01 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics. You'll understand how to implement the most common scenarios in machine learning, such as computer vision, natural language processing (NLP), and sequence modeling for web, mobile, cloud, and embedded runtimes. Most books on machine learning begin with a daunting amount of advanced math. This guide is built on practical lessons that let you work directly with the code. You'll learn: How to build models with TensorFlow using skills that employers desire The basics of machine learning by working with code samples How to implement computer vision, including feature detection in images How to use NLP to tokenize and sequence words and sentences Methods for embedding models in Android and iOS How to serve models over the web and in the cloud with TensorFlow Serving

Machine Learning Design Patterns

Author : Valliappa Lakshmanan
Publisher : O'Reilly Media
ISBN 13 : 1098115759
Total Pages : 408 pages
Book Rating : 4.0/5 (981 download)

DOWNLOAD NOW!

Book Synopsis Machine Learning Design Patterns by : Valliappa Lakshmanan

Download or read book Machine Learning Design Patterns written by Valliappa Lakshmanan and published by O'Reilly Media. This book was released on 2020-10-15 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns codify the experience of hundreds of experts into straightforward, approachable advice. In this book, you will find detailed explanations of 30 patterns for data and problem representation, operationalization, repeatability, reproducibility, flexibility, explainability, and fairness. Each pattern includes a description of the problem, a variety of potential solutions, and recommendations for choosing the best technique for your situation. You'll learn how to: Identify and mitigate common challenges when training, evaluating, and deploying ML models Represent data for different ML model types, including embeddings, feature crosses, and more Choose the right model type for specific problems Build a robust training loop that uses checkpoints, distribution strategy, and hyperparameter tuning Deploy scalable ML systems that you can retrain and update to reflect new data Interpret model predictions for stakeholders and ensure models are treating users fairly

Fundamentals of Deep Learning

Author : Nikhil Buduma
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491925566
Total Pages : 365 pages
Book Rating : 4.4/5 (919 download)

DOWNLOAD NOW!

Book Synopsis Fundamentals of Deep Learning by : Nikhil Buduma

Download or read book Fundamentals of Deep Learning written by Nikhil Buduma and published by "O'Reilly Media, Inc.". This book was released on 2017-05-25 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that’s paving the way for modern machine learning. In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field. Companies such as Google, Microsoft, and Facebook are actively growing in-house deep-learning teams. For the rest of us, however, deep learning is still a pretty complex and difficult subject to grasp. If you’re familiar with Python, and have a background in calculus, along with a basic understanding of machine learning, this book will get you started. Examine the foundations of machine learning and neural networks Learn how to train feed-forward neural networks Use TensorFlow to implement your first neural network Manage problems that arise as you begin to make networks deeper Build neural networks that analyze complex images Perform effective dimensionality reduction using autoencoders Dive deep into sequence analysis to examine language Learn the fundamentals of reinforcement learning

Sourdough

Author : Robin Sloan
Publisher : MCD
ISBN 13 : 0374716439
Total Pages : 273 pages
Book Rating : 4.3/5 (747 download)

DOWNLOAD NOW!

Book Synopsis Sourdough by : Robin Sloan

Download or read book Sourdough written by Robin Sloan and published by MCD. This book was released on 2017-09-05 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: From Robin Sloan, the New York Times bestselling author of Mr. Penumbra’s 24-Hour Bookstore, comes Sourdough, "a perfect parable for our times" (San Francisco Magazine): a delicious and funny novel about an overworked and under-socialized software engineer discovering a calling and a community as a baker. Named One of the Best Books of the Year by NPR, the San Francisco Chronicle, and Southern Living Lois Clary is a software engineer at General Dexterity, a San Francisco robotics company with world-changing ambitions. She codes all day and collapses at night, her human contact limited to the two brothers who run the neighborhood hole-in-the-wall from which she orders dinner every evening. Then, disaster! Visa issues. The brothers quickly close up shop. But they have one last delivery for Lois: their culture, the sourdough starter used to bake their bread. She must keep it alive, they tell her—feed it daily, play it music, and learn to bake with it. Lois is no baker, but she could use a roommate, even if it is a needy colony of microorganisms. Soon, not only is she eating her own homemade bread, she’s providing loaves to the General Dexterity cafeteria every day. Then the company chef urges her to take her product to the farmer’s market—and a whole new world opens up.

MultiMedia Modeling

Author : Yong Man Ro
Publisher : Springer Nature
ISBN 13 : 3030377342
Total Pages : 838 pages
Book Rating : 4.0/5 (33 download)

DOWNLOAD NOW!

Book Synopsis MultiMedia Modeling by : Yong Man Ro

Download or read book MultiMedia Modeling written by Yong Man Ro and published by Springer Nature. This book was released on 2019-12-27 with total page 838 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNCS 11961 and 11962 constitutes the thoroughly refereed proceedings of the 25th International Conference on MultiMedia Modeling, MMM 2020, held in Daejeon, South Korea, in January 2020. Of the 171 submitted full research papers, 40 papers were selected for oral presentation and 46 for poster presentation; 28 special session papers were selected for oral presentation and 8 for poster presentation; in addition, 9 demonstration papers and 6 papers for the Video Browser Showdown 2020 were accepted. The papers of LNCS 11961 are organized in the following topical sections: audio and signal processing; coding and HVS; color processing and art; detection and classification; face; image processing; learning and knowledge representation; video processing; poster papers; the papers of LNCS 11962 are organized in the following topical sections: poster papers; AI-powered 3D vision; multimedia analytics: perspectives, tools and applications; multimedia datasets for repeatable experimentation; multi-modal affective computing of large-scale multimedia data; multimedia and multimodal analytics in the medical domain and pervasive environments; intelligent multimedia security; demo papers; and VBS papers.

Computational Intelligence in Music, Sound, Art and Design

Author : Anikó Ekárt
Publisher : Springer
ISBN 13 : 3030166678
Total Pages : 261 pages
Book Rating : 4.0/5 (31 download)

DOWNLOAD NOW!

Book Synopsis Computational Intelligence in Music, Sound, Art and Design by : Anikó Ekárt

Download or read book Computational Intelligence in Music, Sound, Art and Design written by Anikó Ekárt and published by Springer. This book was released on 2019-04-10 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th International Conference on Evolutionary Computation in Combinatorial Optimization, EvoMUSART 2019, held in Leipzig, Germany, in April 2019, co-located with the Evo*2019 events EuroGP, EvoCOP and EvoApplications. The 16 revised full papers presented were carefully reviewed and selected from 24 submissions. The papers cover a wide range of topics and application areas, including: visual art and music generation, analysis, and interpretation; sound synthesis; architecture; video; poetry; design; and other creative tasks.

Foundations of Deep Reinforcement Learning

Author : Laura Graesser
Publisher : Addison-Wesley Professional
ISBN 13 : 0135172489
Total Pages : 625 pages
Book Rating : 4.1/5 (351 download)

DOWNLOAD NOW!

Book Synopsis Foundations of Deep Reinforcement Learning by : Laura Graesser

Download or read book Foundations of Deep Reinforcement Learning written by Laura Graesser and published by Addison-Wesley Professional. This book was released on 2019-11-20 with total page 625 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Contemporary Introduction to Deep Reinforcement Learning that Combines Theory and Practice Deep reinforcement learning (deep RL) combines deep learning and reinforcement learning, in which artificial agents learn to solve sequential decision-making problems. In the past decade deep RL has achieved remarkable results on a range of problems, from single and multiplayer games—such as Go, Atari games, and DotA 2—to robotics. Foundations of Deep Reinforcement Learning is an introduction to deep RL that uniquely combines both theory and implementation. It starts with intuition, then carefully explains the theory of deep RL algorithms, discusses implementations in its companion software library SLM Lab, and finishes with the practical details of getting deep RL to work. This guide is ideal for both computer science students and software engineers who are familiar with basic machine learning concepts and have a working understanding of Python. Understand each key aspect of a deep RL problem Explore policy- and value-based algorithms, including REINFORCE, SARSA, DQN, Double DQN, and Prioritized Experience Replay (PER) Delve into combined algorithms, including Actor-Critic and Proximal Policy Optimization (PPO) Understand how algorithms can be parallelized synchronously and asynchronously Run algorithms in SLM Lab and learn the practical implementation details for getting deep RL to work Explore algorithm benchmark results with tuned hyperparameters Understand how deep RL environments are designed Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

Formalized Music

Author : Iannis Xenakis
Publisher : Pendragon Press
ISBN 13 : 9781576470794
Total Pages : 410 pages
Book Rating : 4.4/5 (77 download)

DOWNLOAD NOW!

Book Synopsis Formalized Music by : Iannis Xenakis

Download or read book Formalized Music written by Iannis Xenakis and published by Pendragon Press. This book was released on 1992 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pendragon Press is proud to offer this new, revised, and expanded edition of Formalized Music, Iannis Xenakis's landmark book of 1971. In addition to three totally new chapters examining recent breakthroughs in music theory, two original computer programs illustrating the actual realization of newly proposed methods of composition, and an appendix of the very latest developments of stochastic synthesis as an invitation to future exploration, Xenakis offers a very critical self-examination of his theoretical propositions and artistic output of the past thirty-five years. This edition of Formalized Music is an essential tool for understanding the man and the thought processes of one of this century's most important and revolutionary musical figures.

Python Deep Learning

Author : Valentino Zocca
Publisher : Packt Publishing Ltd
ISBN 13 : 1786460661
Total Pages : 406 pages
Book Rating : 4.7/5 (864 download)

DOWNLOAD NOW!

Book Synopsis Python Deep Learning by : Valentino Zocca

Download or read book Python Deep Learning written by Valentino Zocca and published by Packt Publishing Ltd. This book was released on 2017-04-28 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take your machine learning skills to the next level by mastering Deep Learning concepts and algorithms using Python. About This Book Explore and create intelligent systems using cutting-edge deep learning techniques Implement deep learning algorithms and work with revolutionary libraries in Python Get real-world examples and easy-to-follow tutorials on Theano, TensorFlow, H2O and more Who This Book Is For This book is for Data Science practitioners as well as aspirants who have a basic foundational understanding of Machine Learning concepts and some programming experience with Python. A mathematical background with a conceptual understanding of calculus and statistics is also desired. What You Will Learn Get a practical deep dive into deep learning algorithms Explore deep learning further with Theano, Caffe, Keras, and TensorFlow Learn about two of the most powerful techniques at the core of many practical deep learning implementations: Auto-Encoders and Restricted Boltzmann Machines Dive into Deep Belief Nets and Deep Neural Networks Discover more deep learning algorithms with Dropout and Convolutional Neural Networks Get to know device strategies so you can use deep learning algorithms and libraries in the real world In Detail With an increasing interest in AI around the world, deep learning has attracted a great deal of public attention. Every day, deep learning algorithms are used broadly across different industries. The book will give you all the practical information available on the subject, including the best practices, using real-world use cases. You will learn to recognize and extract information to increase predictive accuracy and optimize results. Starting with a quick recap of important machine learning concepts, the book will delve straight into deep learning principles using Sci-kit learn. Moving ahead, you will learn to use the latest open source libraries such as Theano, Keras, Google's TensorFlow, and H20. Use this guide to uncover the difficulties of pattern recognition, scaling data with greater accuracy and discussing deep learning algorithms and techniques. Whether you want to dive deeper into Deep Learning, or want to investigate how to get more out of this powerful technology, you'll find everything inside. Style and approach Python Machine Learning by example follows practical hands on approach. It walks you through the key elements of Python and its powerful machine learning libraries with the help of real world projects.