Download or read book 2018 First International Conference on Secure Cyber Computing and Communication ICSCCC written by IEEE Staff and published by . This book was released on 2018-12-15 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: It includes Object oriented analysis, continuous process modelling and improvement, cost estimation and project planning and effectiveness of agile lean practices, Web Engineering, Quality Management, Managing Software Projects, Multimedia and Visual Software Engineering, Software Maintenance and Testing, Languages and Formal Methods, Web based Education Systems and Learning Applications, Software Engineering Decision Making This track focuses on Natural language processing, artificial intelligence, and computational linguistics with respect to the interactions between computers and human languages It includes Genetic Algorithms, Grammatical Evolution, Differential Evolution, Probabilistic Meta heuristic, Swarm Intelligence, Ant Colony Algorithms, Artificial Immune Systems, High Performance Computing and Computational Intelligence, Fuzzy Logic, Bayesian statistical methods, Neural Networks, Multi Agent Systems, Stochastic Optimization It also focuses on focuses on Cloud and its servi

Download or read book Head First Python written by Paul Barry and published by "O'Reilly Media, Inc.". This book was released on 2016-11-21 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Want to learn the Python language without slogging your way through how-to manuals? With Head First Python, you’ll quickly grasp Python’s fundamentals, working with the built-in data structures and functions. Then you’ll move on to building your very own webapp, exploring database management, exception handling, and data wrangling. If you’re intrigued by what you can do with context managers, decorators, comprehensions, and generators, it’s all here. This second edition is a complete learning experience that will help you become a bonafide Python programmer in no time. Why does this book look so different? Based on the latest research in cognitive science and learning theory, Head First Pythonuses a visually rich format to engage your mind, rather than a text-heavy approach that puts you to sleep. Why waste your time struggling with new concepts? This multi-sensory learning experience is designed for the way your brain really works.

Download or read book Machine Learning Solutions written by Jalaj Thanaki and published by Packt Publishing Ltd. This book was released on 2018-04-27 with total page 567 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical, hands-on solutions in Python to overcome any problem in Machine Learning Key Features Master the advanced concepts, methodologies, and use cases of machine learning Build ML applications for analytics, NLP and computer vision domains Solve the most common problems in building machine learning models Book Description Machine learning (ML) helps you find hidden insights from your data without the need for explicit programming. This book is your key to solving any kind of ML problem you might come across in your job. You’ll encounter a set of simple to complex problems while building ML models, and you'll not only resolve these problems, but you’ll also learn how to build projects based on each problem, with a practical approach and easy-to-follow examples. The book includes a wide range of applications: from analytics and NLP, to computer vision domains. Some of the applications you will be working on include stock price prediction, a recommendation engine, building a chat-bot, a facial expression recognition system, and many more. The problem examples we cover include identifying the right algorithm for your dataset and use cases, creating and labeling datasets, getting enough clean data to carry out processing, identifying outliers, overftting datasets, hyperparameter tuning, and more. Here, you'll also learn to make more timely and accurate predictions. In addition, you'll deal with more advanced use cases, such as building a gaming bot, building an extractive summarization tool for medical documents, and you'll also tackle the problems faced while building an ML model. By the end of this book, you'll be able to fine-tune your models as per your needs to deliver maximum productivity. What you will learn Select the right algorithm to derive the best solution in ML domains Perform predictive analysis effciently using ML algorithms Predict stock prices using the stock index value Perform customer analytics for an e-commerce platform Build recommendation engines for various domains Build NLP applications for the health domain Build language generation applications using different NLP techniques Build computer vision applications such as facial emotion recognition Who this book is for This book is for the intermediate users such as machine learning engineers, data engineers, data scientists, and more, who want to solve simple to complex machine learning problems in their day-to-day work and build powerful and efficient machine learning models. A basic understanding of the machine learning concepts and some experience with Python programming is all you need to get started with this book.

Download or read book Stock Market Prediction Using Machine Learning written by Prince Vipulbhai Patel and published by . This book was released on 2021 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stock market trading has gained popularity in today's world with the advancement in technology and social media. With the help of today's technology we can aim to predict the stock market for the future value of stocks. To make informed predictions, time series analysis is used by most stock brokers around the world. This paper explains and analyzes the prediction of a stock by using machine learning. In this paper, I propose a machine learning approach that will be trained from the available stock data by using acquired knowledge for a prediction with accuracy. In this context, the study will use a machine learning technique called Support Vector Machine (SVM) and Long Short term memory (LSTM) to predict stock prices.

Download or read book Handbook of Research on Smart Technology Models for Business and Industry written by Thomas, J. Joshua and published by IGI Global. This book was released on 2020-06-19 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in machine learning techniques and ever-increasing computing power has helped create a new generation of hardware and software technologies with practical applications for nearly every industry. As the progress has, in turn, excited the interest of venture investors, technology firms, and a growing number of clients, implementing intelligent automation in both physical and information systems has become a must in business. Handbook of Research on Smart Technology Models for Business and Industry is an essential reference source that discusses relevant abstract frameworks and the latest experimental research findings in theory, mathematical models, software applications, and prototypes in the area of smart technologies. Featuring research on topics such as digital security, renewable energy, and intelligence management, this book is ideally designed for machine learning specialists, industrial experts, data scientists, researchers, academicians, students, and business professionals seeking coverage on current smart technology models.

Download or read book Machine Learning Algorithms written by Giuseppe Bonaccorso and published by Packt Publishing Ltd. This book was released on 2017-07-24 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guide About This Book Get started in the field of Machine Learning with the help of this solid, concept-rich, yet highly practical guide. Your one-stop solution for everything that matters in mastering the whats and whys of Machine Learning algorithms and their implementation. Get a solid foundation for your entry into Machine Learning by strengthening your roots (algorithms) with this comprehensive guide. Who This Book Is For This book is for IT professionals who want to enter the field of data science and are very new to Machine Learning. Familiarity with languages such as R and Python will be invaluable here. What You Will Learn Acquaint yourself with important elements of Machine Learning Understand the feature selection and feature engineering process Assess performance and error trade-offs for Linear Regression Build a data model and understand how it works by using different types of algorithm Learn to tune the parameters of Support Vector machines Implement clusters to a dataset Explore the concept of Natural Processing Language and Recommendation Systems Create a ML architecture from scratch. In Detail As the amount of data continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of Big Data and Data Science. The main challenge is how to transform data into actionable knowledge. In this book you will learn all the important Machine Learning algorithms that are commonly used in the field of data science. These algorithms can be used for supervised as well as unsupervised learning, reinforcement learning, and semi-supervised learning. A few famous algorithms that are covered in this book are Linear regression, Logistic Regression, SVM, Naive Bayes, K-Means, Random Forest, TensorFlow, and Feature engineering. In this book you will also learn how these algorithms work and their practical implementation to resolve your problems. This book will also introduce you to the Natural Processing Language and Recommendation systems, which help you run multiple algorithms simultaneously. On completion of the book you will have mastered selecting Machine Learning algorithms for clustering, classification, or regression based on for your problem. Style and approach An easy-to-follow, step-by-step guide that will help you get to grips with real -world applications of Algorithms for Machine Learning.

Download or read book Stock Market Prediction Using Machine Learning and Deep Learning written by Amir Ebrahimi and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last century, the stock market has had several notable growths and declines. Prediction and analysis of financial markets, such as Stock Market prediction, have always been challenging for investors worldwide due to the non-linear nature of financial markets. With the help of Data Science, Machine Learning, and Deep Learning, prediction in Stock Market has become feasible and more reliable. This research aims to find the most accurate models for Stock Market prediction by utilizing machine learning and deep learning algorithms, such as Support Vector Regression (SVR), Long Short-term Memory (LSTM), and Random Forest Regression. Several technical analysis indicators are utilized in the models as features to improve the accuracy of the models. In addition, several transactional signals are generated and used as input features into each prediction model. Our models' training and testing performance are evaluated using Root-Mean-Square Error (RMSE) to find the average error for each model. The evaluations indicate how the models are efficient for predicting the stock price.

Download or read book Stock Market Price Prediction using Machine Learning Techniques written by Mahfuz Islam Khan Jabed and published by Ocleno. This book was released on 2024-02-16 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: Predicting stock market prices is a challenging task in the financial sector, where the Efficient Market Hypothesis (EMH) posits the impossibility of accurate prediction due to the inherent uncertainty and complexity of stock price behaviour. However, introducing Machine Learning algorithms has shown the feasibility of stock market price forecasting. This study employs advanced Machine Learning models that can predict stock price movements with the right level of accuracy if the correct parameter tuning and appropriate predictor models are developed. In this research work, the LSTM model, which is a type of Recurrent Neural Network (RNN), time series forecasting Facebook Prophet algorithm and Random Forest Regressor model have been implemented on 10 Dhaka Stock Market (DSEbd) listed companies and six international giants for predicting the stock and forecasting the future price. The dataset of domestic companies is extracted from the graphical representation of the DSEbd website, and the international companies' dataset is imported from Yahoo Finance. In this experiment, Facebook Prophet demonstrates a long period of forecasting with reasonable accuracy, capturing daily, weekly, and yearly seasonality, including holiday effects for market trend analysis. Remarkably, the LSTM model exhibits significant accuracy, yielding the best results with evaluation metrics, including RMSE (0.35), MAPE (0.50%), and MAE (0.30). The experimental results underscore the efficiency of LSTM for future stock forecasting, observed over 15 days of upcoming market prices. A comparison of the results shows that the LSTM model efficiently forecasts the next day's closing price.

Download or read book Information Technology and Systems written by Álvaro Rocha and published by Springer. This book was released on 2019-01-28 with total page 976 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features a selection of articles from The 2019 International Conference on Information Technology & Systems (ICITS’19), held at the Universidad de Las Fuerzas Armadas, in Quito, Ecuador, on 6th to 8th February 2019. ICIST is a global forum for researchers and practitioners to present and discuss recent findings and innovations, current trends, professional experiences and challenges of modern information technology and systems research, together with their technological development and applications. The main topics covered are: information and knowledge management; organizational models and information systems; software and systems modeling; software systems, architectures, applications and tools; multimedia systems and applications; computer networks, mobility and pervasive systems; intelligent and decision support systems; big data analytics and applications; human–computer interaction; ethics, computers & security; health informatics; information technologies in education; cybersecurity and cyber-defense; electromagnetics, sensors and antennas for security.

Download or read book Stock Market Prediction and Efficiency Analysis using Recurrent Neural Network written by Joish Bosco and published by GRIN Verlag. This book was released on 2018-09-18 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt: Project Report from the year 2018 in the subject Computer Science - Technical Computer Science, , course: Computer Science, language: English, abstract: Modeling and Forecasting of the financial market have been an attractive topic to scholars and researchers from various academic fields. The financial market is an abstract concept where financial commodities such as stocks, bonds, and precious metals transactions happen between buyers and sellers. In the present scenario of the financial market world, especially in the stock market, forecasting the trend or the price of stocks using machine learning techniques and artificial neural networks are the most attractive issue to be investigated. As Giles explained, financial forecasting is an instance of signal processing problem which is difficult because of high noise, small sample size, non-stationary, and non-linearity. The noisy characteristics mean the incomplete information gap between past stock trading price and volume with a future price. The stock market is sensitive with the political and macroeconomic environment. However, these two kinds of information are too complex and unstable to gather. The above information that cannot be included in features are considered as noise. The sample size of financial data is determined by real-world transaction records. On one hand, a larger sample size refers a longer period of transaction records; on the other hand, large sample size increases the uncertainty of financial environment during the 2 sample period. In this project, we use stock data instead of daily data in order to reduce the probability of uncertain noise, and relatively increase the sample size within a certain period of time. By non-stationarity, one means that the distribution of stock data is various during time changing. Non-linearity implies that feature correlation of different individual stocks is various. Efficient Market Hypothesis was developed by Burton G. Malkiel in 1991.

Download or read book 2021 5th International Conference on Information Systems and Computer Networks ISCON written by Institute of Electrical and Electronics Engineers and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Data Mining Algorithms written by Pawel Cichosz and published by John Wiley & Sons. This book was released on 2015-01-27 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining Algorithms is a practical, technically-oriented guide to data mining algorithms that covers the most important algorithms for building classification, regression, and clustering models, as well as techniques used for attribute selection and transformation, model quality evaluation, and creating model ensembles. The author presents many of the important topics and methodologies widely used in data mining, whilst demonstrating the internal operation and usage of data mining algorithms using examples in R.

Download or read book Proceedings of International Conference on Intelligent Computing Information and Control Systems written by A. Pasumpon Pandian and published by Springer Nature. This book was released on 2021-01-24 with total page 972 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of papers presented at the International Conference on Intelligent Computing, Information and Control Systems (ICICCS 2020). It encompasses various research works that help to develop and advance the next-generation intelligent computing and control systems. The book integrates the computational intelligence and intelligent control systems to provide a powerful methodology for a wide range of data analytics issues in industries and societal applications. The book also presents the new algorithms and methodologies for promoting advances in common intelligent computing and control methodologies including evolutionary computation, artificial life, virtual infrastructures, fuzzy logic, artificial immune systems, neural networks and various neuro-hybrid methodologies. This book is pragmatic for researchers, academicians and students dealing with mathematically intransigent problems.

Download or read book Challenges and Applications of Data Analytics in Social Perspectives written by Sathiyamoorthi, V. and published by IGI Global. This book was released on 2020-12-04 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: With exponentially increasing amounts of data accumulating in real-time, there is no reason why one should not turn data into a competitive advantage. While machine learning, driven by advancements in artificial intelligence, has made great strides, it has not been able to surpass a number of challenges that still prevail in the way of better success. Such limitations as the lack of better methods, deeper understanding of problems, and advanced tools are hindering progress. Challenges and Applications of Data Analytics in Social Perspectives provides innovative insights into the prevailing challenges in data analytics and its application on social media and focuses on various machine learning and deep learning techniques in improving practice and research. The content within this publication examines topics that include collaborative filtering, data visualization, and edge computing. It provides research ideal for data scientists, data analysts, IT specialists, website designers, e-commerce professionals, government officials, software engineers, social media analysts, industry professionals, academicians, researchers, and students.

Download or read book Machine Learning and Metaheuristics Algorithms and Applications written by Sabu M. Thampi and published by Springer Nature. This book was released on 2021-02-05 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second Symposium on Machine Learning and Metaheuristics Algorithms, and Applications, SoMMA 2020, held in Chennai, India, in October 2020. Due to the COVID-19 pandemic the conference was held online. The 12 full papers and 7 short papers presented in this volume were thoroughly reviewed and selected from 40 qualified submissions. The papers cover such topics as machine learning, artificial intelligence, Internet of Things, modeling and simulation, disctibuted computing methodologies, computer graphics, etc.

Download or read book Machine Learning for Asset Management written by Emmanuel Jurczenko and published by John Wiley & Sons. This book was released on 2020-10-06 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new edited volume consists of a collection of original articles written by leading financial economists and industry experts in the area of machine learning for asset management. The chapters introduce the reader to some of the latest research developments in the area of equity, multi-asset and factor investing. Each chapter deals with new methods for return and risk forecasting, stock selection, portfolio construction, performance attribution and transaction costs modeling. This volume will be of great help to portfolio managers, asset owners and consultants, as well as academics and students who want to improve their knowledge of machine learning in asset management.

Download or read book ICDSMLA 2019 written by Amit Kumar and published by Springer Nature. This book was released on 2020-05-19 with total page 2010 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers selected high-impact articles from the 1st International Conference on Data Science, Machine Learning & Applications 2019. It highlights the latest developments in the areas of Artificial Intelligence, Machine Learning, Soft Computing, Human–Computer Interaction and various data science & machine learning applications. It brings together scientists and researchers from different universities and industries around the world to showcase a broad range of perspectives, practices and technical expertise.