Web development with Django : learn to build modern web applications with a Python-based framework

Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and KerasKey FeaturesImplement machine learning algorithms to build, train, and validate algorithmic modelsCreate your own algorithmic design process to apply probabilistic machine learning approaches to trading decisionsDevelop neural networks for algorithmic trading to perform time series forecasting and smart analyticsBook DescriptionThe explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies.This book shows how to access market, fundamental, and alternative data via API or web scraping and offers a framework to evaluate alternative data. You'll practice the ML workflow from model design, loss metric definition, and parameter tuning to performance evaluation in a time series context. You will understand ML algorithms such as Bayesian and ensemble methods and manifold learning, and will know how to train and tune these models using pandas, statsmodels, sklearn, PyMC3, xgboost, lightgbm, and catboost. This book also teaches you how to extract features from text data using spaCy, classify news and assign sentiment scores, and to use gensim to model topics and learn word embeddings from financial reports. You will also build and evaluate neural networks, including RNNs and CNNs, using Keras and PyTorch to exploit unstructured data for sophisticated strategies.Finally, you will apply transfer learning to satellite images to predict economic activity and use reinforcement learning to build agents that learn to trade in the OpenAI Gym.What you will learnImplement machine learning techniques to solve investment and trading problemsLeverage market, fundamental, and alternative data to research alpha factorsDesign and fine-tune supervised, unsupervised, and reinforcement learning modelsOptimize portfolio risk and performance using pandas, NumPy, and scikit-learnIntegrate machine learning models into a live trading strategy on QuantopianEvaluate strategies using reliable backtesting methodologies for time seriesDesign and evaluate deep neural networks using Keras, PyTorch, and TensorFlowWork with reinforcement learning for trading strategies in the OpenAI GymWho this book is forHands-On Machine Learning for Algorithmic Trading is for data analysts, data scientists, and Python developers, as well as investment analysts and portfolio managers working within the finance and investment industry. If you want to perform efficient algorithmic trading by developing smart investigating strategies using machine learning algorithms, this is the book for you. Some understanding of Python and machine learning techniques is mandatory. Understanding and coding advanced deep learning algorithms with the most intuitive deep learning library in existenceKey FeaturesExplore the most advanced deep learning techniques that drive modern AI resultsImplement deep neural networks, autoencoders, GANs, VAEs, and deep reinforcement learningA wide study of GANs, including Improved GANs, Cross-Domain GANs, and Disentangled Representation GANsBook DescriptionRecent developments in deep learning, including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Deep Reinforcement Learning (DRL) are creating impressive AI results in our news headlines - such as AlphaGo Zero beating world chess champions, and generative AI that can create art paintings that sell for over $400k because they are so human-like. Advanced Deep Learning with Keras is a comprehensive guide to the advanced deep learning techniques available today, so you can create your own cutting-edge AI. Using Keras as an open-source deep learning library, you'll find hands-on projects throughout that show you how to create more effective AI with the latest techniques. The journey begins with an overview of MLPs, CNNs, and RNNs, which are the building blocks for the more advanced techniques in the book. You'll learn how to implement deep learning models with Keras and TensorFlow 1.x, and move forwards to advanced techniques, as you explore deep neural network architectures, including ResNet and DenseNet, and how to create autoencoders. You then learn all about GANs, and how they can open new levels of AI performance. Next, you'll get up to speed with how VAEs are implemented, and you'll see how GANs and VAEs have the generative power to synthesize data that can be extremely convincing to humans - a major stride forward for modern AI. To complete this set of advanced techniques, you'll learn how to implement DRL such as Deep Q-Learning and Policy Gradient Methods, which are critical to many modern results in AI.What you will learnCutting-edge techniques in human-like AI performanceImplement advanced deep learning models using KerasThe building blocks for advanced techniques - MLPs, CNNs, and RNNsDeep neural networks – ResNet and DenseNetAutoencoders and Variational Autoencoders (VAEs)Generative Adversarial Networks (GANs) and creative AI techniquesDisentangled Representation GANs, and Cross-Domain GANsDeep reinforcement learning methods and implementationProduce industry-standard applications using OpenAI GymDeep Q-Learning and Policy Gradient MethodsWho this book is forSome fluency with Python is assumed. As an advanced book, you'll be familiar with some machine learning approaches, and some practical experience with DL will be helpful. Knowledge of Keras or TensorFlow 1.x is not required but would be helpful. A comprehensive guide to advanced deep learning techniques, including Autoencoders, GANs, VAEs, and Deep Reinforcement Learning, that drive today's most impressive AI results Key Features Explore the most advanced deep learning techniques that drive modern AI results Implement Deep Neural Networks, Autoencoders, GANs, VAEs, and Deep Reinforcement Learning A wide study of GANs, including Improved GANs, Cross-Domain GANs and Disentangled Representation GANs Book Description Recent developments in deep learning, including GANs, Variational Autoencoders, and Deep Reinforcement Learning, are creating impressive AI results in our news headlines - such as AlphaGo Zero beating world chess champions, and generative AI that can create art paintings that sell for over $400k because they are so human-like. Advanced Deep Learning with Keras is a comprehensive guide to the advanced deep learning techniques available today, so you can create your own cutting-edge AI. Using Keras as an open-source deep learning library, you'll find hands-on projects throughout that show you how to create more effective AI with the latest techniques. The journey begins with an overview of MLPs, CNNs, and RNNs, which are the building blocks for the more advanced techniques in the book. You'll learn how to implement deep learning models with Keras and Tensorflow, and move forwards to advanced techniques, as you explore deep neural network architectures, including ResNet and DenseNet, and how to create Autoencoders. You then learn all about Generative Adversarial Networks (GANs), and how they can open new levels of AI performance. Variational AutoEncoders (VAEs) are implemented, and you'll see how GANs and VAEs have the generative power to synthesize data that can be extremely convincing to humans - a major stride forward for modern AI. To complete this set of advanced techniques, you'll learn how to implement Deep Reinforcement Learning (DRL) such as Deep Q-Learning and Policy Gradient Methods, which are critical to many modern results in AI. What you will learn Cutting-edge techniques in human-like AI performance Implement advanced deep learning models using Keras The building blocks for advanced techniques - MLPs, CNNs, and RNNs Deep neural networks - ResNet and DenseNet Autoencoders and Variational AutoEncoders (VAEs) Generative Adversarial Networks (GANs) and creative AI techniques Disentangled Representation GANs, and Cross-Domain GANs Deep Reinforcement Learning (DRL) meth .. Cut through the noise and get real results with a step-by-step approach to learning SQL Key Features A structured, straightforward introduction to SQL for beginners A SQL tutorial with step-by-step exercises and activities that help build key skills Structured to let you progress at your own pace, on your own terms Use your physical print copy to redeem free access to the online interactive edition Book Description You already know you want to learn SQL, and the best way to learn SQL is to learn by doing. The SQL Workshop focuses on building up your SQL database management skills so that you can easily store and retrieve data or become the in-house expert on complex queries. You'll learn from real examples that lead to real results. Throughout The SQL Workshop, you'll take an engaging step-by-step approach to understanding SQL programming. You won't have to sit through any unnecessary theory. If you're short on time you can jump into a single exercise each day or spend an entire weekend learning how to create functions and stored procedures. It's your choice. Learning on your terms, you'll build up and reinforce key skills in a way that feels rewarding. Every physical print copy of The SQL Workshop unlocks access to the interactive edition. With videos detailing all exercises and activities, you'll always have a guided solution. You can also benchmark yourself against assessments, track progress, and receive content updates. You'll even earn a secure credential that you can share and verify online upon completion. It's a premium learning experience that's included with your printed copy. To redeem, follow the instructions located at the start of your book. Fast-paced and direct, The SQL Workshop is the ideal companion for SQL beginners. You'll build and iterate on your code like a software developer, learning along the way. This process means that you'll find that your new skills stick, embedded as best practice. A solid foundation for the years ahead. What you will learn Learn how to create normalized databases Explore how to insert data into tables efficiently Explore various techniques to retrieve data from multiple tables Build advanced queries using techniques like subqueries and views Learn advanced SQL programming techniques such as functions and triggers Who this book is for Our goal at Packt is to help you be successful, in whatever it is you choose to do. The SQL Workshop is an ideal SQL tutorial for the SQL beginner who is just gett .. Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras Key Features Implement machine learning algorithms to build, train, and validate algorithmic models Create your own algorithmic design process to apply probabilistic machine learning approaches to trading decisions Develop neural networks for algorithmic trading to perform time series forecasting and smart analytics Book Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies. This book shows how to access market, fundamental, and alternative data via API or web scraping and offers a framework to evaluate alternative data. You'll practice the ML workflow from model design, loss metric definition, and parameter tuning to performance evaluation in a time series context. You will understand ML algorithms such as Bayesian and ensemble methods and manifold learning, and will know how to train and tune these models using pandas, statsmodels, sklearn, PyMC3, xgboost, lightgbm, and catboost. This book also teaches you how to extract features from text data using spaCy, classify news and assign sentiment scores, and to use gensim to model topics and learn word embeddings from financial reports. You will also build and evaluate neural networks, including RNNs and CNNs, using Keras and PyTorch to exploit unstructured data for sophisticated strategies. Finally, you will apply transfer learning to satellite images to predict economic activity and use reinforcement learning to build agents that learn to trade in the OpenAI Gym. What you will learn Implement machine learning techniques to solve investment and trading problems Leverage market, fundamental, and alternative data to research alpha factors Design and fine-tune supervised, unsupervised, and reinforcement learning models Optimize portfolio risk and performance using pandas, NumPy, and scikit-learn Integrate machine learning models into a live trading strategy on Quantopian Evaluate strategies using reliable backtesting methodologies for time series Design and evaluate deep neural networks using Keras, PyTorch, and TensorFlow Work with reinforcement learning for trading strategies in the OpenAI Gym Who this book is for Hands-On M.. Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras Key Features Implement machine learning algorithms to build, train, and validate algorithmic models Create your own algorithmic design process to apply probabilistic machine learning approaches to trading decisions Develop neural networks for algorithmic trading to perform time series forecasting and smart analytics Book Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies. This book shows how to access market, fundamental, and alternative data via API or web scraping and offers a framework to evaluate alternative data. You'll practice the ML work?ow from model design, loss metric definition, and parameter tuning to performance evaluation in a time series context. You will understand ML algorithms such as Bayesian and ensemble methods and manifold learning, and will know how to train and tune these models using pandas, statsmodels, sklearn, PyMC3, xgboost, lightgbm, and catboost. This book also teaches you how to extract features from text data using spaCy, classify news and assign sentiment scores, and to use gensim to model topics and learn word embeddings from financial reports. You will also build and evaluate neural networks, including RNNs and CNNs, using Keras and PyTorch to exploit unstructured data for sophisticated strategies. Finally, you will apply transfer learning to satellite images to predict economic activity and use reinforcement learning to build agents that learn to trade in the OpenAI Gym. What you will learn Implement machine learning techniques to solve investment and trading problems Leverage market, fundamental, and alternative data to research alpha factors Design and fine-tune supervised, unsupervised, and reinforcement learning models Optimize portfolio risk and performance using pandas, NumPy, and scikit-learn Integrate machine learning models into a live trading strategy on Quantopian Evaluate strategies using reliable backtesting methodologies for time series Design and evaluate deep neural networks using Keras, PyTorch, and TensorFlow Work with reinforcement learning for trading strategies in the OpenAI Gym Who this book is for Hands-On Ma.. Get to grips with SQL fundamentals and learn how to efficiently create, read and update information stored in databasesKey FeaturesUnderstand the features and syntax of SQL and use them to query databasesLearn how to create databases and tables and manipulate the data within themCreate advanced queries and apply them on realistic databases with hands-on activitiesBook DescriptionMany software applications are backed by powerful relational database systems, meaning that the skills to be able to maintain a SQL database and reliably retrieve data are in high demand. With its simple syntax and effective data manipulation capabilities, SQL enables you to manage relational databases with ease. The SQL Workshop will help you progress from basic to advanced-level SQL queries in order to create and manage databases successfully.This Workshop begins with an introduction to basic CRUD commands and gives you an overview of the different data types in SQL. You'll use commands for narrowing down the search results within a database and learn about data retrieval from single and multiple tables in a single query. As you advance, you'll use aggregate functions to perform calculations on a set of values, and implement process automation using stored procedures, functions, and triggers. Finally, you'll secure your database against potential threats and use access control to keep your data safe.Throughout this Workshop, you'll use your skills on a realistic database for an online shop, preparing you for solving data problems in the real world.By the end of this book, you'll have built the knowledge, skills and confidence to creatively solve real-world data problems with SQL.What you will learnCreate databases and insert data into themUse SQL queries to create, read, update, and delete dataMaintain data integrity and consistency through normalizationCustomize your basic SQL queries to get the desired outputRefine your database search using the WHERE and HAVING clausesUse joins to fetch data from multiple tables and create custom reportsImprove web application performance by automating processesSecure a database with GRANT and REVOKE privilegesWho this book is forThis Workshop is suitable for anyone who wants to learn how to use SQL to work with databases. No prior SQL or database experience is necessary. Whether you're an aspiring software developer, database engineer, data scientist, or systems administrator, this Workshop will quickly get you up and running. Learn How To Create Your Own Websites Simply, Safely, And Quickly With Django By Tackling Practical Activities Based On Realistic Case Studies Key Features Understand Django Functionality And The Model-view-template (mvt) Paradigm Create And Iteratively Build A Book Review Website, Adding Features As You Build Your Knowledge Explore Advanced Concepts Such As Rest Api Implementation And Third-party Module Integration Book Description Do You Want To Develop Reliable And Secure Applications Which Stand Out From The Crowd, Rather Than Spending Hours On Boilerplate Code? Then The Django Framework Is Where You Should Begin. Often Referred To As A 'batteries Included' Web Development Framework, Django Comes With All The Core Features Needed To Build A Standalone Application. Web Development With Django Takes This Philosophy And Equips You With The Knowledge And Confidence To Build Real-world Applications Using Python. Starting With The Essential Concepts Of Django, You'll Cover Its Major Features By Building A Website Called Bookr - A Repository For Book Reviews. This End-to-end Case Study Is Split Into A Series Of Bitesize Projects That Are Presented As Exercises And Activities, Allowing You To Challenge Yourself In An Enjoyable And Attainable Way. As You Progress, You'll Learn Various Practical Skills, Including How To Serve Static Files To Add Css, Javascript, And Images To Your Application, How To Implement Forms To Accept User Input, And How To Manage Sessions To Ensure A Reliable User Experience. Throughout This Book, You'll Cover Key Daily Tasks That Are Part Of The Development Cycle Of A Real-world Web Application. By The End Of This Book, You'll Have The Skills And Confidence To Creatively Tackle Your Own Ambitious Projects With Django. What You Will Learn Create A New Application And Add Models To Describe Your Data Use Views And Templates To Control Behavior And Appearance Implement Access Control Through Authentication And Permissions Develop Practical Web Forms To Add Features Such As File Uploads Develop A Restful Api And Javascript Code That Communicates With It Connect To A Database Such As Postgresql Who This Book Is For Web Development With Django Is Designed For Programmers Who Want To Gain Web Development Skills With The Django Framework. To Fully Understand The Concepts Explained In This Book, You Must Have Basic Knowledge Of Python Programming, As Well As Familiarity With Javascript, Html, And Css. It's Christmas time and Holden Caulfield has just been expelled from yet another school... Fleeing the crooks at Pencey Prep, he pinballs around New York City seeking solace in fleeting encountersshooting the bull with strangers in dive hotels, wandering alone round Central Park, getting beaten up by pimps and cut down by erstwhile girlfriends. The city is beautiful and terrible, in all its neon loneliness and seedy glamour, its mingled sense of possibility and emptiness. Holden passes through it like a ghost, thinking always of his kid sister Phoebe, the only person who really understands him, and his determination to escape the phonies and find a life of true meaning. The Catcher in the Rye is an all-time classic in coming-of-age literature- an elegy to teenage alienation, capturing the deeply human need for connection and the bewildering sense of loss as we leave childhood behind. (https://www.goodreads.com/author/show/819789.J_D__Salinger_s) J.D. Salinger's (19192010) classic novel of teenage angst and rebellion was first published in 1951. The novel was included on Time 's 2005 list of the 100 best English-language novels written since 1923. It was named by Modern Library and its readers as one of the 100 best English-language novels of the 20th century. It has been frequently challenged in the court for its liberal use of profanity and portrayal of sexuality and in the 1950's and 60's it was the novel that every teenage boy wants to read. "The hero-narrator of 'The Catcher in the Rye' is an ancient child of sixteen, a native New Yorker named Holden Caulfield. Through circumstances that tend to preclude adult, secondhand description, he leaves his prep school in Pennsylvania and goes underground in New York City for three days. The boy himself is at once too simple and too complex for us to make any final comment about him or his story. Perhaps the safest thing we can say about Holden is that he was born in the world not just strongly attracted to beauty but, almost, hopelessly impaled on it. There are many voices in this novel: children's voices, adult voices, underground voices -- but Holden's voice is the most eloquent of all. Transcending his own vernacular, yet remaining marvelously faithful to it, he issues a perfectly articulated cry of mixed pain and pleasure. However, like most lovers and clowns and poets of the higher orders, he keeps most of the pain to, and for, himself. The pleasure he gives away, or sets aside, with all his heart. It is there for the reader who can handle it to keep"--Jacket On a brisk autumn day, a twelve-year-old boy stands on the shores of the gray Atlantic, near a silent amusement park and a fading ocean resort called the Alhambra. The past has driven Jack Sawyer here: his father is gone, his mother is dying, and the world no longer makes sense. But for Jack everything is about to change. For he has been chosen to make a journey back across America--and into another realm Twelve-year-old Jack Sawyer takes on a quest in this and a parallel world, the "Territories," to acquire a mystical talisman that will save the life of his dying mother and her "twinner," the Queen of the Territories. Jack "flips" back and forth between worlds during his journey, finding his way through and past representatives of good and evil in both With the help of this book, you'll build smart algorithmic models using machine learning algorithms covering tasks such as time series forecasting, backtesting, trade predictions, and more using easy-to-follow examples. By the end, you'll be able to adopt algorithmic trading in your own business and implement intelligent investigative strategies. This book covers advanced deep learning techniques to create successful AI. Using MLPs, CNNs, and RNNs as building blocks to more advanced techniques, you'll study deep neural network architectures, Autoencoders, Generative Adversarial Networks (GANs), Variational AutoEncoders (VAEs), and Deep Reinforcement Learning (DRL) critical to many ... Filled with practical examples and realistic exercises, The SQL Workshop will get you up to speed with the fundamentals of SQL. You'll learn how to use SQL queries and functions to create and manage relational databases, and apply your new skills to creatively solve real-world problems. Story of Holden Caufield with his idiosyncrasies, penetrating insight, confusion, sensitivity and negativism. Holden, knowing he is to be expelled from school, decides to leave early. He spends three days in New York City and tells the story of what he did and suffered there. The Talisman is a 1984 fantasy novel by American writers Stephen King and Peter Straub. The Talisman was nominated for both the Locus and World Fantasy Awards in 1985. King and Straub followed up with a sequel, Black House (2001). Followed by: Black House ON SEPTEMBER 15th, 1981, a boy named Jack Sawyer stood where the water and land come together, hands in the pockets of his jeans, looking out at the steady Atlantic. Jack Sawyer, a twelve-year-old boy, begins a terrifying quest for the Talisman--for only the Talisman can save his dying mother and defeat their enemy In an effort to escape the hypocrisies of life at his boarding school, sixteen-year-old Holden Caulfield seeks refuge in New York City. J.d. Salinger. Originally Published In Hardcover By Little, Brown And Company, July 1951-- T.p. Verso.