Machine Learning Blueprints With Python
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Blueprints For Text Analytics Using Python
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Author : Jens Albrecht
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2020-12-04
Blueprints For Text Analytics Using Python written by Jens Albrecht and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-04 with Computers categories.
Turning text into valuable information is essential for businesses looking to gain a competitive advantage. With recent improvements in natural language processing (NLP), users now have many options for solving complex challenges. But it's not always clear which NLP tools or libraries would work for a business's needs, or which techniques you should use and in what order. This practical book provides data scientists and developers with blueprints for best practice solutions to common tasks in text analytics and natural language processing. Authors Jens Albrecht, Sidharth Ramachandran, and Christian Winkler provide real-world case studies and detailed code examples in Python to help you get started quickly. Extract data from APIs and web pages Prepare textual data for statistical analysis and machine learning Use machine learning for classification, topic modeling, and summarization Explain AI models and classification results Explore and visualize semantic similarities with word embeddings Identify customer sentiment in product reviews Create a knowledge graph based on named entities and their relations
Machine Learning Blueprints With Python
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Author : Charles Spark
language : en
Publisher: Independently Published
Release Date : 2025-12-09
Machine Learning Blueprints With Python written by Charles Spark and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-12-09 with Computers categories.
Unlock the power of machine learning with Python and transform your ideas into real-world applications! Machine Learning Blueprints with Python: From Model Training to Real-World Deployment is your ultimate hands-on guide to mastering AI and ML, designed for beginners and experienced practitioners alike. Written by Charles Spark, this comprehensive book demystifies the entire ML lifecycle, providing reusable "blueprints"-step-by-step templates and workflows-that you can adapt to any project. Dive into Python essentials and key libraries like NumPy, Pandas, Scikit-learn, TensorFlow, and Keras. Learn to source and prepare data, perform exploratory analysis, and build supervised models for regression and classification. Explore unsupervised techniques like clustering and dimensionality reduction, then advance to deep learning with neural networks, CNNs for images, and LSTMs for time series. Optimize your models with hyperparameter tuning, ensemble methods, and bias mitigation, and discover real-world deployment strategies using Flask, FastAPI, Docker, and Kubernetes. Packed with practical case studies-from predictive maintenance in manufacturing to sentiment analysis and stock forecasting-this book bridges theory and practice. Whether you're a data scientist, software engineer, or aspiring AI enthusiast, you'll gain the tools to deploy scalable, ethical ML solutions. Includes Python code snippets, templates, a glossary, and resources for further study. Start building intelligent systems today and elevate your career in the booming field of machine learning!
Python Machine Learning Blueprints
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Author : Alexander Combs
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-01-31
Python Machine Learning Blueprints written by Alexander Combs and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-31 with Computers categories.
Discover a project-based approach to mastering machine learning concepts by applying them to everyday problems using libraries such as scikit-learn, TensorFlow, and Keras Key FeaturesGet to grips with Python's machine learning libraries including scikit-learn, TensorFlow, and KerasImplement advanced concepts and popular machine learning algorithms in real-world projectsBuild analytics, computer vision, and neural network projects Book Description Machine learning is transforming the way we understand and interact with the world around us. This book is the perfect guide for you to put your knowledge and skills into practice and use the Python ecosystem to cover key domains in machine learning. This second edition covers a range of libraries from the Python ecosystem, including TensorFlow and Keras, to help you implement real-world machine learning projects. The book begins by giving you an overview of machine learning with Python. With the help of complex datasets and optimized techniques, you’ll go on to understand how to apply advanced concepts and popular machine learning algorithms to real-world projects. Next, you’ll cover projects from domains such as predictive analytics to analyze the stock market and recommendation systems for GitHub repositories. In addition to this, you’ll also work on projects from the NLP domain to create a custom news feed using frameworks such as scikit-learn, TensorFlow, and Keras. Following this, you’ll learn how to build an advanced chatbot, and scale things up using PySpark. In the concluding chapters, you can look forward to exciting insights into deep learning and you'll even create an application using computer vision and neural networks. By the end of this book, you’ll be able to analyze data seamlessly and make a powerful impact through your projects. What you will learnUnderstand the Python data science stack and commonly used algorithmsBuild a model to forecast the performance of an Initial Public Offering (IPO) over an initial discrete trading window Understand NLP concepts by creating a custom news feedCreate applications that will recommend GitHub repositories based on ones you’ve starred, watched, or forkedGain the skills to build a chatbot from scratch using PySparkDevelop a market-prediction app using stock dataDelve into advanced concepts such as computer vision, neural networks, and deep learningWho this book is for This book is for machine learning practitioners, data scientists, and deep learning enthusiasts who want to take their machine learning skills to the next level by building real-world projects. The intermediate-level guide will help you to implement libraries from the Python ecosystem to build a variety of projects addressing various machine learning domains. Knowledge of Python programming and machine learning concepts will be helpful.
Python Machine Learning Blueprints
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Author : Alexander Combs
language : en
Publisher: Packt Publishing
Release Date : 2016-07-29
Python Machine Learning Blueprints written by Alexander Combs and has been published by Packt Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-29 with Computers categories.
Python Machine Learning Blueprints Second Edition
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Author : Alexander Combs
language : en
Publisher:
Release Date : 2019
Python Machine Learning Blueprints Second Edition written by Alexander Combs and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
Discover a project-based approach to mastering machine learning concepts by applying them to everyday problems using libraries such as scikit-learn, TensorFlow, and Keras Key Features Get to grips with Python's machine learning libraries including scikit-learn, TensorFlow, and Keras Implement advanced concepts and popular machine learning algorithms in real-world projects Build analytics, computer vision, and neural network projects Book Description Machine learning is transforming the way we understand and interact with the world around us. This book is the perfect guide for you to put your knowledge and skills into practice and use the Python ecosystem to cover key domains in machine learning. This second edition covers a range of libraries from the Python ecosystem, including TensorFlow and Keras, to help you implement real-world machine learning projects. The book begins by giving you an overview of machine learning with Python. With the help of complex datasets and optimized techniques, you'll go on to understand how to apply advanced concepts and popular machine learning algorithms to real-world projects. Next, you'll cover projects from domains such as predictive analytics to analyze the stock market and recommendation systems for GitHub repositories. In addition to this, you'll also work on projects from the NLP domain to create a custom news feed using frameworks such as scikit-learn, TensorFlow, and Keras. Following this, you'll learn how to build an advanced chatbot, and scale things up using PySpark. In the concluding chapters, you can look forward to exciting insights into deep learning and you'll even create an application using computer vision and neural networks. By the end of this book, you'll be able to analyze data seamlessly and make a powerful impact through your projects. What you will learn Understand the Python data science stack and commonly used algorithms Build a model to forecast the performance of an Initial Public Offering (IPO) over an initial discrete trading window Understand NLP concepts by creating a custom news feed Create applications that will recommend GitHub repositories based on ones you've starred, watched, or forked Gain the skills to build a chatbot from scratch using PySpark Develop a market-prediction app using stock data Delve into advanced concepts such as computer vision, neural networks, and deep learning Who this book is for This book is for machine learning practitioners, data scientists, and ...
Blueprints For Text Analytics Using Python
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Author : Jens Albrecht
language : en
Publisher: O'Reilly Media
Release Date : 2020-12-04
Blueprints For Text Analytics Using Python written by Jens Albrecht and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-04 with Computers categories.
Turning text into valuable information is essential for businesses looking to gain a competitive advantage. With recent improvements in natural language processing (NLP), users now have many options for solving complex challenges. But it's not always clear which NLP tools or libraries would work for a business's needs, or which techniques you should use and in what order. This practical book provides data scientists and developers with blueprints for best practice solutions to common tasks in text analytics and natural language processing. Authors Jens Albrecht, Sidharth Ramachandran, and Christian Winkler provide real-world case studies and detailed code examples in Python to help you get started quickly. Extract data from APIs and web pages Prepare textual data for statistical analysis and machine learning Use machine learning for classification, topic modeling, and summarization Explain AI models and classification results Explore and visualize semantic similarities with word embeddings Identify customer sentiment in product reviews Create a knowledge graph based on named entities and their relations
The Freedom Blueprint For A Python Developer
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Author : Barrett Williams
language : en
Publisher: Barrett Williams
Release Date : 2024-08-26
The Freedom Blueprint For A Python Developer written by Barrett Williams and has been published by Barrett Williams this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-26 with Computers categories.
### The Freedom Blueprint for a Python Developer Unlock the secrets to living a life of unparalleled freedom while building a successful career as a Python developer. "The Freedom Blueprint for a Python Developer" is your comprehensive guide to combining the dynamic world of Python programming with the exciting lifestyle of a digital nomad. Whether you're a seasoned coder or a beginner looking to break into the tech industry, this eBook offers a step-by-step roadmap to mastering Python and adopting a remote work lifestyle. **Chapter Highlights** - **Introduction to the Digital Nomad Lifestyle** Explore the growing digital nomad movement, uncover its benefits, and dispel common myths. - **Why Python is the Ideal Language for Digital Nomads** Dive into Python's versatility and discover how it opens doors to remote job opportunities. - **Getting Started with Python** Learn how to set up your development environment and write your first Python program while mastering essential libraries. - **Leveraging ChatGPT for Learning Python** Supercharge your learning with AI-driven assistance from ChatGPT and see practical coding examples. - **Core and Advanced Python Programming Concepts** From variables and data types to object-oriented programming and APIs, gain a deep understanding of Python. - **Building a Portfolio with Python Projects** Identify key projects to showcase your skills and build an impressive portfolio that attracts remote job offers. - **Finding Remote Work as a Python Developer** Navigate the remote job market with tips on building your online presence, networking, and utilizing job boards. - **Freelancing vs. Contracting vs. Full-Time Remote Jobs** Weigh the pros and cons of different work arrangements and choose the best fit for your lifestyle. - **Managing Finances on the Go** Get practical advice on international banking, budgeting, and handling taxes as a nomadic professional. - **Productivity Tips for Remote Python Developers** Optimize your work environment, manage your time effectively, and stay focused amidst distractions. - **Tools and Resources for the Modern Digital Nomad** Discover essential software, online communities, and continuous learning resources. - **Health and Wellness While Traveling** Learn how to maintain physical fitness, prioritize mental health, and balance work with leisure. - **Navigating Cross-Cultural Work Environments** Master cross-cultural communication and adapt to diverse work styles. - **Case Studies Successful Python Digital Nomads** Gain insights from real-life stories and actionable takeaways from experienced digital nomads. Embark on your journey towards freedom, flexibility, and success. Transform your Python skills into a ticket to the digital nomad lifestyle with "The Freedom Blueprint for a Python Developer." Your adventure starts now.
Blueprints For Text Analysis Using Python
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Author : Jens Albrecht
language : en
Publisher:
Release Date : 2020
Blueprints For Text Analysis Using Python written by Jens Albrecht and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Machine learning categories.
Turning text into valuable information is essential for many businesses looking to gain a competitive advantage. There have been many improvements in natural language processing and users have a lot of options when choosing to work on a problem. However, it's not always clear which NLP tools or libraries would work for a business use-or which techniques you should use and in what order. This practical book provides theoretical background and real-world case studies with detailed code examples to help developers and data scientists obtain insight from text online. Authors Jens Albrecht, Sidharth Ramachandran, and Christian Winkler use blueprints for text-related problems that apply state-of-the-art machine learning methods in Python. If you have a fundamental understanding of statistics and machine learning along with basic programming experience in Python, you're ready to get started. You'll learn how to: Crawl and clean then explore and visualize textual data in different formats Preprocess and vectorize text for machine learning Apply methods for classification, topic analysis, summarization, and knowledge extraction Use semantic word embeddings and deep learning approaches for complex problems Work with Python NLP libraries like spaCy, NLTK, and Gensim in combination with scikit-learn, Pandas, and PyTorch.
The Frelancepreneur Success Blueprint
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Author : Dr. Ope Banwo
language : en
Publisher: Dr Ope Banwo
Release Date :
The Frelancepreneur Success Blueprint written by Dr. Ope Banwo and has been published by Dr Ope Banwo this book supported file pdf, txt, epub, kindle and other format this book has been release on with Business & Economics categories.
Welcome to "THE FREELANCEPRENEUR BLUEPRINT, your ultimate guide to building a profitable and sustainable 6-figure freelancing business from the ground up. As a seasoned veteran with over two decades of experience in the freelance world, I’ve distilled my knowledge, insights, and proven strategies into this comprehensive blueprint. Whether you’re a novice just starting out or an established freelancer aiming to scale, this book will equip you with the tools and techniques to achieve unparalleled success.
Machine Learning And Data Science Blueprints For Finance
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Author : Hariom Tatsat
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2020-10-01
Machine Learning And Data Science Blueprints For Finance written by Hariom Tatsat and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-01 with Computers categories.
Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry. You'll examine ML concepts and over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP). Ideal for professionals working at hedge funds, investment and retail banks, and fintech firms, this book also delves deep into portfolio management, algorithmic trading, derivative pricing, fraud detection, asset price prediction, sentiment analysis, and chatbot development. You'll explore real-life problems faced by practitioners and learn scientifically sound solutions supported by code and examples. This book covers: Supervised learning regression-based models for trading strategies, derivative pricing, and portfolio management Supervised learning classification-based models for credit default risk prediction, fraud detection, and trading strategies Dimensionality reduction techniques with case studies in portfolio management, trading strategy, and yield curve construction Algorithms and clustering techniques for finding similar objects, with case studies in trading strategies and portfolio management Reinforcement learning models and techniques used for building trading strategies, derivatives hedging, and portfolio management NLP techniques using Python libraries such as NLTK and scikit-learn for transforming text into meaningful representations