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Author: Gabriel Preda
Publisher: Packt Publishing Ltd
ISBN: 1805125710
Category : Computers
Languages : en
Pages : 371
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Book Description
Printed in Color Develop an array of effective strategies and blueprints to approach any new data analysis on the Kaggle platform and create Notebooks with substance, style and impact Leverage the power of Generative AI with Kaggle Models Purchase of the print or Kindle book includes a free PDF eBook Key Features Master the basics of data ingestion, cleaning, exploration, and prepare to build baseline models Work robustly with any type, modality, and size of data, be it tabular, text, image, video, or sound Improve the style and readability of your Notebooks, making them more impactful and compelling Book DescriptionDeveloping Kaggle Notebooks introduces you to data analysis, with a focus on using Kaggle Notebooks to simultaneously achieve mastery in this fi eld and rise to the top of the Kaggle Notebooks tier. The book is structured as a sevenstep data analysis journey, exploring the features available in Kaggle Notebooks alongside various data analysis techniques. For each topic, we provide one or more notebooks, developing reusable analysis components through Kaggle's Utility Scripts feature, introduced progressively, initially as part of a notebook, and later extracted for use across future notebooks to enhance code reusability on Kaggle. It aims to make the notebooks' code more structured, easy to maintain, and readable. Although the focus of this book is on data analytics, some examples will guide you in preparing a complete machine learning pipeline using Kaggle Notebooks. Starting from initial data ingestion and data quality assessment, you'll move on to preliminary data analysis, advanced data exploration, feature qualifi cation to build a model baseline, and feature engineering. You'll also delve into hyperparameter tuning to iteratively refi ne your model and prepare for submission in Kaggle competitions. Additionally, the book touches on developing notebooks that leverage the power of generative AI using Kaggle Models.What you will learn Approach a dataset or competition to perform data analysis via a notebook Learn data ingestion and address issues arising with the ingested data Structure your code using reusable components Analyze in depth both small and large datasets of various types Distinguish yourself from the crowd with the content of your analysis Enhance your notebook style with a color scheme and other visual effects Captivate your audience with data and compelling storytelling techniques Who this book is for This book is suitable for a wide audience with a keen interest in data science and machine learning, looking to use Kaggle Notebooks to improve their skills and rise in the Kaggle Notebooks ranks. This book caters to: Beginners on Kaggle from any background Seasoned contributors who want to build various skills like ingestion, preparation, exploration, and visualization Expert contributors who want to learn from the Grandmasters to rise into the upper Kaggle rankings Professionals who already use Kaggle for learning and competing
Author: Pandas Notebook
Publisher: Independently Published
ISBN: 9781092438483
Category : Nature
Languages : en
Pages : 112
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Book Description
A Book for people who love pandass. Perfect for keeping track of allpersonal stuff and great gift for christmas and birthdays. 9 inches x 6 inches 110 lined pages
Author: Epic Love Books
Publisher:
ISBN: 9781081892166
Category :
Languages : en
Pages : 102
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Book Description
A cute purple panda bear sits in pretty green grass in front of a rainbow of peace and love on this beautiful journal. This cheerful animal notebook is a gift of joy for someone who likes happiness and fun.
Author: Gabriel Preda
Publisher: Packt Publishing Ltd
ISBN: 1805125710
Category : Computers
Languages : en
Pages : 371
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Book Description
Printed in Color Develop an array of effective strategies and blueprints to approach any new data analysis on the Kaggle platform and create Notebooks with substance, style and impact Leverage the power of Generative AI with Kaggle Models Purchase of the print or Kindle book includes a free PDF eBook Key Features Master the basics of data ingestion, cleaning, exploration, and prepare to build baseline models Work robustly with any type, modality, and size of data, be it tabular, text, image, video, or sound Improve the style and readability of your Notebooks, making them more impactful and compelling Book DescriptionDeveloping Kaggle Notebooks introduces you to data analysis, with a focus on using Kaggle Notebooks to simultaneously achieve mastery in this fi eld and rise to the top of the Kaggle Notebooks tier. The book is structured as a sevenstep data analysis journey, exploring the features available in Kaggle Notebooks alongside various data analysis techniques. For each topic, we provide one or more notebooks, developing reusable analysis components through Kaggle's Utility Scripts feature, introduced progressively, initially as part of a notebook, and later extracted for use across future notebooks to enhance code reusability on Kaggle. It aims to make the notebooks' code more structured, easy to maintain, and readable. Although the focus of this book is on data analytics, some examples will guide you in preparing a complete machine learning pipeline using Kaggle Notebooks. Starting from initial data ingestion and data quality assessment, you'll move on to preliminary data analysis, advanced data exploration, feature qualifi cation to build a model baseline, and feature engineering. You'll also delve into hyperparameter tuning to iteratively refi ne your model and prepare for submission in Kaggle competitions. Additionally, the book touches on developing notebooks that leverage the power of generative AI using Kaggle Models.What you will learn Approach a dataset or competition to perform data analysis via a notebook Learn data ingestion and address issues arising with the ingested data Structure your code using reusable components Analyze in depth both small and large datasets of various types Distinguish yourself from the crowd with the content of your analysis Enhance your notebook style with a color scheme and other visual effects Captivate your audience with data and compelling storytelling techniques Who this book is for This book is suitable for a wide audience with a keen interest in data science and machine learning, looking to use Kaggle Notebooks to improve their skills and rise in the Kaggle Notebooks ranks. This book caters to: Beginners on Kaggle from any background Seasoned contributors who want to build various skills like ingestion, preparation, exploration, and visualization Expert contributors who want to learn from the Grandmasters to rise into the upper Kaggle rankings Professionals who already use Kaggle for learning and competing
Author: PURNA CHANDER RAO KATHULA
Publisher: BPB Publications
ISBN: 9389845653
Category : Computers
Languages : en
Pages : 372
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Book Description
Learn how to use JupyterLab, Numpy, pandas, Scipy, Matplotlib, and Seaborn for Data science Key Features a- Get familiar with different inbuilt Data structures, Functional programming, and Datetime objects. a- Handling heavy Datasets to optimize the data types for memory management, reading files in chunks, dask, and modin pandas. a- Time-series analysis to find trends, seasonality, and cyclic components. Seaborn to build aesthetic plots with high-level interfaces and customized themes. a- Exploratory data analysis with real-time datasets to maximize the insights about data. Description The book will start with quick introductions to Python and its ecosystem libraries for data science such as JupyterLab, Numpy, Pandas, SciPy, Matplotlib, and Seaborn. This book will help in learning python data structures and essential concepts such as Functions, Lambdas, List comprehensions, Datetime objects, etc. required for data engineering. It also covers an in-depth understanding of Python data science packages where JupyterLab used as an IDE for writing, documenting, and executing the python code, Numpy used for computation of numerical operations, Pandas for cleaning and reorganizing the data, handling large datasets and merging the dataframes to get meaningful insights. You will go through the statistics to understand the relation between the variables using SciPy and building visualization charts using Matplotllib and Seaborn libraries. What will you learn a- Learn about Python data containers, their methods, and attributes. a- Learn Numpy arrays for the computation of numerical data. a- Learn Pandas data structures, DataFrames, and Series. a- Learn statistics measures of central tendency, central limit theorem, confidence intervals, and hypothesis testing. a- A brief understanding of visualization, control, and draw different inbuilt charts to extract important variables, detect outliers, and anomalies using Matplotlib and Seaborn. Who this book is for This book is for anyone who wants to use Python for Data Analysis and Visualization. This book is for novices as well as experienced readers with working knowledge of the pandas library. Basic knowledge of Python is a must. Table of Contents 1. Introduction to Data Analysis 2. Jupyter lab 3. Python overview 4. Introduction to Numpy 5. Introduction to Pandas 6. Data Analysis 7. Time-Series Analysis 8. Introduction to Statistics 9. Matplotlib 10. Seaborn 11. Exploratory Data Analysis About the Author Purna Chander Rao.Kathula is a Data Science enthusiast, Data Manager, Seasoned Programmer, and a Technical trainer, with around 17+ years of experience in a vast array of languages, including Perl, C, C++, Java, and Python and wide variety set of domains like Insurance, Adtech, Storage, Gaming, Mobility, Big Data, and Analytics. He is a certified Applied Data Science with Python Specialization, from Coursera, University of Michigan. He graduated from the College of Engineering G.I.T.A.M with a degree in Mechanical Engineering. He is a frequent speaker at DataScience and Data Engineering user groups, and he regularly delivers webinars and conducts training on Hadoop, Big data, Data Analysis, and Visualization technologies. Your Blog links https://blog.imaginea.com/author/purna-chander-rao-kathula/ https://www.slideshare.net/PurnaChander1 https://www.slideshare.net/sriganesha/hive-and-data-analysis-using-pandas Your LinkedIn Profile: https://www.linkedin.com/in/purna-chander-rao-kathula-043852a/
Author: ASHISH KUMAR SHYAMAKRISHNA SIDDHARTH CHAMARTHY RAMYA RAMACHANDRAN RAGHAV AGARWAL
Publisher: DeepMisti Publication
ISBN: 9360444804
Category : Computers
Languages : en
Pages : 176
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Book Description
In the ever-evolving landscape of the modern world, the synergy between technology and management has become a cornerstone of innovation and progress. This book, Cloud Computing Architecture: Design, Implementation, and Security Strategies, is conceived to bridge the gap between emerging technological advancements in cloud computing and their strategic application in modern IT management. Our objective is to equip readers with the tools and insights necessary to excel in this dynamic intersection of fields. This book is structured to provide a comprehensive exploration of the methodologies and strategies that define the innovation of cloud technologies, particularly in terms of architecture, implementation, and security. From foundational theories to advanced applications, we delve into the critical aspects that drive successful cloud-based solutions in enterprise environments. We have made a concerted effort to present complex concepts in a clear and accessible manner, making this work suitable for a diverse audience, including students, IT managers, and industry professionals. In authoring this book, we have drawn upon the latest research and best practices to ensure that readers not only gain a robust theoretical understanding but also acquire practical skills that can be applied in real-world cloud computing scenarios. The chapters are designed to strike a balance between depth and breadth, covering topics ranging from technological development and cloud architecture design to the strategic management of security in cloud-based systems. Additionally, we emphasize the importance of effective communication, dedicating sections to the art of presenting innovative ideas and solutions in a precise and academically rigorous manner. The inspiration for this book arises from a recognition of the crucial role that cloud computing architecture and security strategies play in shaping the future of digital businesses. We are profoundly grateful to Chancellor Shri Shiv Kumar Gupta of Maharaja Agrasen Himalayan Garhwal University for his unwavering support and vision. His dedication to fostering academic excellence and promoting a culture of innovation has been instrumental in bringing this project to fruition. We hope this book will serve as a valuable resource and inspiration for those eager to deepen their understanding of how cloud computing technologies and management practices can be harnessed together to drive innovation. We believe that the knowledge and insights contained within these pages will empower readers to lead the way in creating secure, scalable cloud solutions that will define the future of enterprise IT. Thank you for joining us on this journey. Authors
Author: Yves Hilpisch
Publisher: John Wiley & Sons
ISBN: 111903793X
Category : Business & Economics
Languages : en
Pages : 376
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Book Description
Supercharge options analytics and hedging using the power ofPython Derivatives Analytics with Python shows you how toimplement market-consistent valuation and hedging approaches usingadvanced financial models, efficient numerical techniques, and thepowerful capabilities of the Python programming language. Thisunique guide offers detailed explanations of all theory, methods,and processes, giving you the background and tools necessary tovalue stock index options from a sound foundation. You'll find anduse self-contained Python scripts and modules and learn how toapply Python to advanced data and derivatives analytics as youbenefit from the 5,000+ lines of code that are provided to help youreproduce the results and graphics presented. Coverage includesmarket data analysis, risk-neutral valuation, Monte Carlosimulation, model calibration, valuation, and dynamic hedging, withmodels that exhibit stochastic volatility, jump components,stochastic short rates, and more. The companion website featuresall code and IPython Notebooks for immediate execution andautomation. Python is gaining ground in the derivatives analytics space,allowing institutions to quickly and efficiently deliver portfolio,trading, and risk management results. This book is the financeprofessional's guide to exploiting Python's capabilities forefficient and performing derivatives analytics. Reproduce major stylized facts of equity and options marketsyourself Apply Fourier transform techniques and advanced Monte Carlopricing Calibrate advanced option pricing models to market data Integrate advanced models and numeric methods to dynamicallyhedge options Recent developments in the Python ecosystem enable analysts toimplement analytics tasks as performing as with C or C++, but usingonly about one-tenth of the code or even less. DerivativesAnalytics with Python — Data Analysis, Models, Simulation,Calibration and Hedging shows you what you need to know tosupercharge your derivatives and risk analytics efforts.
Author: RAJESH TIRUPATH SATISH KRISHNAMURTHY RAMYA RAMACHANDRAN PROF. (DR) PUNIT GOEL
Publisher: DeepMisti Publication
ISBN: 9360447234
Category : Computers
Languages : en
Pages : 169
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Book Description
In the ever-evolving landscape of the modern world, the synergy between technology and management has become a cornerstone of innovation and progress. This book, Neural Networks Unleashed: From Basics to Advanced Models, is conceived to bridge the gap between emerging technological advancements in neural networks and their strategic application across industries. Our objective is to equip readers with the tools and insights necessary to excel in this dynamic intersection of fields. This book is structured to provide a comprehensive exploration of the methodologies and strategies that define neural networks, from foundational theories to advanced applications. We delve into the critical aspects that drive successful innovation in fields such as computer vision, natural language processing, and AI-driven automation. We have made a concerted effort to present complex concepts in a clear and accessible manner, making this work suitable for a diverse audience, including students, engineers, managers, and industry professionals. In authoring this book, we have drawn upon the latest research and best practices to ensure that readers not only gain a robust theoretical understanding but also acquire practical skills that can be applied in real-world scenarios. The chapters are designed to strike a balance between depth and breadth, covering topics ranging from neural network architectures and training techniques to their strategic management and application in various industries. Additionally, we emphasize the importance of effective communication, dedicating sections to the art of presenting innovative ideas and solutions in a precise and academically rigorous manner. The inspiration for this book arises from a recognition of the crucial role that neural networks play in shaping the future of technology and business. We are profoundly grateful to Chancellor Shri Shiv Kumar Gupta of Maharaja Agrasen Himalayan Garhwal University for his unwavering support and vision. His dedication to fostering academic excellence and promoting a culture of innovation has been instrumental in bringing this project to fruition. We hope this book will serve as a valuable resource and inspiration for those eager to deepen their understanding of how neural networks can be harnessed to drive innovation. We believe that the knowledge and insights contained within these pages will empower readers to lead the way in creating innovative solutions that will define the future of technology. Thank you for joining us on this journey. Authors
Author: Penny Guisinger
Publisher: U of Nebraska Press
ISBN: 1496238907
Category : Biography & Autobiography
Languages : en
Pages : 190
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Book Description
"A collection of memories throughout Penny Guisinger's life recounting her story of sexuality, love, and marriage"--
Author: Rob Botwright
Publisher: Rob Botwright
ISBN: 1839386258
Category : Computers
Languages : en
Pages : 261
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Book Description
Introducing the Ultimate AI Book Bundle: Deep Learning, Computer Vision, Python Machine Learning, and Neural Networks Are you ready to embark on an exhilarating journey into the world of artificial intelligence, deep learning, and computer vision? Look no further! Our carefully curated book bundle, "DEEP LEARNING: COMPUTER VISION, PYTHON MACHINE LEARNING AND NEURAL NETWORKS," offers you a comprehensive roadmap to AI mastery. BOOK 1 - DEEP LEARNING DEMYSTIFIED: A BEGINNER'S GUIDE 🚀 Perfect for beginners, this book dismantles the complexities of deep learning. From neural networks to Python programming, you'll build a strong foundation in AI. BOOK 2 - MASTERING COMPUTER VISION WITH DEEP LEARNING 🌟 Dive into the captivating world of computer vision. Unlock the secrets of image processing, convolutional neural networks (CNNs), and object recognition. Harness the power of visual intelligence! BOOK 3 - PYTHON MACHINE LEARNING AND NEURAL NETWORKS: FROM NOVICE TO PRO 📊 Elevate your skills with this intermediate volume. Delve into data preprocessing, supervised and unsupervised learning, and become proficient in training neural networks. BOOK 4 - ADVANCED DEEP LEARNING: CUTTING-EDGE TECHNIQUES AND APPLICATIONS 🔥 Ready to conquer advanced techniques? Learn optimization strategies, tackle common deep learning challenges, and explore real-world applications shaping the future. 🎉 What You'll Gain: · A strong foundation in deep learning · Proficiency in computer vision · Mastery of Python machine learning · Advanced deep learning skills · Real-world application knowledge · Cutting-edge AI insights 📚 Why Choose Our Book Bundle? · Expertly curated content · Beginner to expert progression · Clear explanations and hands-on examples · Comprehensive coverage of AI topics · Practical real-world applications · Stay ahead with emerging AI trends 🌐 Who Should Grab This Bundle? · Beginners eager to start their AI journey · Intermediate learners looking to expand their skill set · Experts seeking advanced deep learning insights · Anyone curious about AI's limitless possibilities 📦 Limited-Time Offer: Get all four books in one bundle and save! Don't miss this chance to accelerate your AI knowledge and skills. 🔒 Secure Your AI Mastery: Click "Add to Cart" now and embark on an educational adventure that will redefine your understanding of artificial intelligence. Your journey to AI excellence begins here!
Author: Dattaraj Rao
Publisher: John Wiley & Sons
ISBN: 1119564875
Category : Computers
Languages : en
Pages : 324
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Book Description
Build a Keras model to scale and deploy on a Kubernetes cluster We have seen an exponential growth in the use of Artificial Intelligence (AI) over last few years. AI is becoming the new electricity and is touching every industry from retail to manufacturing to healthcare to entertainment. Within AI, were seeing a particular growth in Machine Learning (ML) and Deep Learning (DL) applications. ML is all about learning relationships from labeled (Supervised) or unlabeled data (Unsupervised). DL has many layers of learning and can extract patterns from unstructured data like images, video, audio, etc. em style="box-sizing: border-box;"Keras to Kubernetes: The Journey of a Machine Learning Model to Production takes you through real-world examples of building DL models in Keras for recognizing product logos in images and extracting sentiment from text. You will then take that trained model and package it as a web application container before learning how to deploy this model at scale on a Kubernetes cluster. You will understand the different practical steps involved in real-world ML implementations which go beyond the algorithms. Find hands-on learning examples Learn to uses Keras and Kubernetes to deploy Machine Learning models Discover new ways to collect and manage your image and text data with Machine Learning Reuse examples as-is to deploy your models Understand the ML model development lifecycle and deployment to production If youre ready to learn about one of the most popular DL frameworks and build production applications with it, youve come to the right place!
