Data Science Bookcamp
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Data Science Bookcamp
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Author : Leonard Apeltsin
language : en
Publisher: Simon and Schuster
Release Date : 2021-11-30
Data Science Bookcamp written by Leonard Apeltsin and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-30 with Computers categories.
Subtitle on cover: five real-world Python projects.
Data Science Bookcamp
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Author : Leonard Apeltsin
language : en
Publisher:
Release Date : 2021
Data Science Bookcamp written by Leonard Apeltsin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
Data Science Bookcamp doesn't stop with surface-level theory and toy examples. As you work through each project, you'll learn how to troubleshoot common problems like missing data, messy data, and algorithms that don't quite fit the model you're building. You'll appreciate the detailed setup instructions and the fully explained solutions that highlight common failure points. In the end, you'll be confident in your skills because you can see the results.
Machine Learning Bookcamp
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Author : Alexey Grigorev
language : en
Publisher: Simon and Schuster
Release Date : 2021-11-23
Machine Learning Bookcamp written by Alexey Grigorev and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-23 with Computers categories.
Master key machine learning concepts as you build actual projects! Machine learning is what you need for analyzing customer behavior, predicting price trends, evaluating risk, and much more. To master ML, you need great examples, clear explanations, and lots of practice. This book delivers all three! Machine learning bookcamp presents realistic, practical machine learning scenarios, along with crystal-clear coverage of key concepts. In it, you'll complete engaging projects, such as creating a car price predictor using linear regression and deploying a churn prediction service. You'll go beyond the algorithms and explore important techniques like deploying ML applications on serverless systems and serving models with Kubernetes and Kubeflow. Dig in, get your hands dirty, and have fun building your ML skills!
Data Science Bootcamp
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Author : Jasmine Harper
language : en
Publisher: Independently Published
Release Date : 2024-03-04
Data Science Bootcamp written by Jasmine Harper and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-04 with Computers categories.
Embark on Your Data Science Journey! "Data Science Bootcamp: From Zero to Hero in Data Science" offers a comprehensive pathway for those aspiring to become expert data scientists. This meticulously crafted book serves as a rigorous bootcamp, providing learners of all levels the capacities to dive deep into the vast ocean of data science. Whether you are a beginner with a curiosity in data or an intermediate practitioner aiming to solidify your expertise, this book caters to your ambition with precision and depth. The book unfolds the mysteries of data science across 12 chapters, encompassing crucial topics from introductory concepts to advanced data manipulation and analysis techniques. Alongside theoretical insights, you'll engage with practical exercises, real-world case studies, and emerging trends in data science, equipping you with the holistic understanding needed to thrive in this dynamic field. By weaving together the fundamentals with cutting-edge methodologies, "Data Science Bootcamp" ensures your learning journey is both enlightening and actionable. It bridges the gap between academic concepts and their real-world applications, facilitating a smooth transition from learning to implementing. Discover the transformative power of data analysis, machine learning algorithms, and predictive modeling in shaping industries and driving innovation. Don't miss out on this unique opportunity to elevate your data science prowess. Embrace the challenge, harness the power of data, and embark on a rewarding career as a data scientist. With "Data Science Bootcamp," the road from beginner to hero in data science is engaging, accessible, and filled with invaluable insights. Make this pivotal leap today. Your journey through data science starts here! Table of Contents 1. Introduction to Data Science - The Essence of Data Science - Skills Needed for a Data Scientist - Understanding Data and Its Power 2. Data Wrangling and Cleaning - Fundamentals of Data Wrangling - Cleaning Data: Techniques and Importance - Practical Exercises in Data Cleaning 3. Exploratory Data Analysis - Introduction to EDA - Visualizing Data - Finding Patterns in Data 4. Statistical Foundations - Basic Statistical Concepts - Applying Statistics in Data Science - Statistical Tests and Their Importance 5. Machine Learning Basics - Understanding Machine Learning - Supervised vs. Unsupervised Learning - Building Your First Machine Learning Model 6. Advanced Machine Learning - Fine-Tuning ml Models - Dealing with Overfitting and Underfitting - Introduction to Deep Learning 7. Data Visualization - The Power of Data Visualization - Tools for Visualizing Data - Creating Engaging Visuals 8. Big Data and Its Applications - Understanding Big Data - Big Data Technologies - Applications of Big Data in Various Industries 9. Predictive Modeling - Introduction to Predictive Modeling - Building Predictive Models - Real-World Applications of Predictive Modeling 10. Natural Language Processing - Basics of NLP - Implementing NLP in data Science Projects - Advanced NLP Techniques 11. Ethical Considerations in Data Science - The Importance of Ethics - Data Privacy and Security - Fairness and Bias in Machine Learning 12. Career Path and Next Steps - Building a Portfolio - Preparing for Data Science Interviews - Continuous Learning and Growth in Data Science
Feature Engineering Bookcamp
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Author : Sinan Ozdemir
language : en
Publisher: Simon and Schuster
Release Date : 2022-10-18
Feature Engineering Bookcamp written by Sinan Ozdemir and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-18 with Computers categories.
Deliver huge improvements to your machine learning pipelines without spending hours fine-tuning parameters! This book’s practical case-studies reveal feature engineering techniques that upgrade your data wrangling—and your ML results. In Feature Engineering Bookcamp you will learn how to: Identify and implement feature transformations for your data Build powerful machine learning pipelines with unstructured data like text and images Quantify and minimize bias in machine learning pipelines at the data level Use feature stores to build real-time feature engineering pipelines Enhance existing machine learning pipelines by manipulating the input data Use state-of-the-art deep learning models to extract hidden patterns in data Feature Engineering Bookcamp guides you through a collection of projects that give you hands-on practice with core feature engineering techniques. You’ll work with feature engineering practices that speed up the time it takes to process data and deliver real improvements in your model’s performance. This instantly-useful book skips the abstract mathematical theory and minutely-detailed formulas; instead you’ll learn through interesting code-driven case studies, including tweet classification, COVID detection, recidivism prediction, stock price movement detection, and more. About the technology Get better output from machine learning pipelines by improving your training data! Use feature engineering, a machine learning technique for designing relevant input variables based on your existing data, to simplify training and enhance model performance. While fine-tuning hyperparameters or tweaking models may give you a minor performance bump, feature engineering delivers dramatic improvements by transforming your data pipeline. About the book Feature Engineering Bookcamp walks you through six hands-on projects where you’ll learn to upgrade your training data using feature engineering. Each chapter explores a new code-driven case study, taken from real-world industries like finance and healthcare. You’ll practice cleaning and transforming data, mitigating bias, and more. The book is full of performance-enhancing tips for all major ML subdomains—from natural language processing to time-series analysis. What's inside Identify and implement feature transformations Build machine learning pipelines with unstructured data Quantify and minimize bias in ML pipelines Use feature stores to build real-time feature engineering pipelines Enhance existing pipelines by manipulating input data About the reader For experienced machine learning engineers familiar with Python. About the author Sinan Ozdemir is the founder and CTO of Shiba, a former lecturer of Data Science at Johns Hopkins University, and the author of multiple textbooks on data science and machine learning. Table of Contents 1 Introduction to feature engineering 2 The basics of feature engineering 3 Healthcare: Diagnosing COVID-19 4 Bias and fairness: Modeling recidivism 5 Natural language processing: Classifying social media sentiment 6 Computer vision: Object recognition 7 Time series analysis: Day trading with machine learning 8 Feature stores 9 Putting it all together
Python Bookcamp
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Author : Vaskaran Sarcar
language : en
Publisher:
Release Date : 2021-01-16
Python Bookcamp written by Vaskaran Sarcar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-16 with categories.
Python Bookcamp: Exercises and Projects is a beginner''s book. It is a quick programming guide to the Python programming language. The best way of learning is by doing exercises and projects. Therefore, this book follows the boot camp approach. It enables you to make interesting programs in no time.The world is changing, and we keep extra features developing, but the core concepts are evergreen. We build all additional features on top of those. If you have a sound foundation, you can adopt the upcoming features quickly. You also understand the reason behibrnd those changes. So, the book focuses on core topics in-depth, but it does not cover "A-Z" in Python at the same time. The book has 12 chapters. The first chapter is a simple warm-up session for you. Here you''ll set up your programming environment. The second chapter talks about the Python basics. Here you learn about variables, operators, and comments. Each subsequent chapter contains exercises and hands-on projects for you. As you move on, these projects will be more complex. You implement the case studies using the concepts you learn in a previous chapter. At the beginning of these chapters, you get a description of the projects. Once you finish reading these chapters, you get the complete solutions.The book covers both the common and the advanced data types along with the topic of loop and decision making. It also covers file handling, functions, and modules with exception handling mechanisms too. The last chapters of this book cover the object-oriented programming basics. Here you see the usage of classes, objects, and inheritance. You''ll also learn about static and class methods in Python. In the end, there is a chapter to show you how to write useful tests to verify your code. In most cases, you''ll see the complete programs with output. It means you can continue reading the material without interruption. To write the very short programs, or to test the simple commands, I use a Python command shell. For the remaining cases, you see the usage of PyCharm Community Edition in a Windows10 environment. This is a very popular IDE, and this version is free at the time of this writing. Many of us are afraid of fat books. They do not promise that you can complete the book in one day or 7 days, etc. Here is the twist. You should not forget that learning is a continuous process. We can achieve no real mastery in a short period. So, the motto of the book is "To learn the core topics in Python, whatever efforts I need to put, I am OK with that". I believe that if you have a strong focus, you can complete one chapter in a day with no trouble. So, the simple arithmetic says that you can complete the book in 12 days. But it is secondary! I have designed the book in such a way that upon completion of the book, you will learn the core concepts in depth. And you''ll know how to learn further. In short, you can pick the book if the answer is "yes" to the following questions: *Have you never programmed before, but eager to learn Python? *Do you want to explore the Python essentials step-by-step, but as quickly as possible? *Do you have experience with a high-level programming languages, but want to learn Python ? *Do you know how to install software on a machine and then set up the coding environment? *Do you like to review your knowledge before you use Python in advanced fields such as data science, machine learning? Probably you shouldn''t read this book if the answer is yes to any of the following questions: *Are you confident about the fundamentals of Python? *Are you looking for advanced concepts in Python only? *Do you dislike a book that has an emphasis on exercises? *"I dislike Windows OS, and PyCharm. I want to learn and use Python without them only."-is this statement true for you? The source code and other details are available at https://github.com/Vaskaran/PythonBookcamp
Wildlife Research Report
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Author :
language : en
Publisher:
Release Date : 2013
Wildlife Research Report written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Game protection categories.
Python Projects For Beginners
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Author : Connor P. Milliken
language : en
Publisher: Apress
Release Date : 2019-11-15
Python Projects For Beginners written by Connor P. Milliken and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-15 with Computers categories.
Immerse yourself in learning Python and introductory data analytics with this book’s project-based approach. Through the structure of a ten-week coding bootcamp course, you’ll learn key concepts and gain hands-on experience through weekly projects. Each chapter in this book is presented as a full week of topics, with Monday through Thursday covering specific concepts, leading up to Friday, when you are challenged to create a project using the skills learned throughout the week. Topics include Python basics and essential intermediate concepts such as list comprehension, generators and iterators, understanding algorithmic complexity, and data analysis with pandas. From beginning to end, this book builds up your abilities through exercises and challenges, culminating in your solid understanding of Python. Challenge yourself with the intensity of a coding bootcamp experience or learn at your own pace. With this hands-on learning approach, you will gain the skills you need to jumpstart a new career in programming or further your current one as a software developer. What You Will Learn Understand beginning and more advanced concepts of the Python language Be introduced to data analysis using pandas, the Python Data Analysis library Walk through the process of interviewing and answering technical questions Create real-world applications with the Python language Learn how to use Anaconda, Jupyter Notebooks, and the Python Shell Who This Book Is For Those trying to jumpstart a new career into programming, and those already in the software development industry and would like to learn Python programming.
Newsweek
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Author :
language : en
Publisher:
Release Date : 2004
Newsweek written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Business and politics categories.
Dive Into Data Science
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Author : Bradford Tuckfield
language : en
Publisher: No Starch Press
Release Date : 2023-07-04
Dive Into Data Science written by Bradford Tuckfield and has been published by No Starch Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-04 with Computers categories.
Learn how to use data science and Python to solve everyday business problems. Dive into the exciting world of data science with this practical introduction. Packed with essential skills and useful examples, Dive Into Data Science will show you how to obtain, analyze, and visualize data so you can leverage its power to solve common business challenges. With only a basic understanding of Python and high school math, you’ll be able to effortlessly work through the book and start implementing data science in your day-to-day work. From improving a bike sharing company to extracting data from websites and creating recommendation systems, you’ll discover how to find and use data-driven solutions to make business decisions. Topics covered include conducting exploratory data analysis, running A/B tests, performing binary classification using logistic regression models, and using machine learning algorithms. You’ll also learn how to: Forecast consumer demand Optimize marketing campaigns Reduce customer attrition Predict website traffic Build recommendation systems With this practical guide at your fingertips, harness the power of programming, mathematical theory, and good old common sense to find data-driven solutions that make a difference. Don’t wait; dive right in!