D'autres livres qui pourraient vous intéresser

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  Breathe Easy - An overview of...

  Dr. Camysha Wright MD PA

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  Breathe Easy is a comprehensive guide to recognizing, treating, and preventing allergy and inflammation-related illnesses, including sinusitis, asthma, and nasal obstruction, and explores the various causes of these conditions, their symptoms, and the treatment options available.

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  Ultimate Parallel and...

  Nabanita Dash

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  Unleash Julia’s power: Code Your Data Stories, Shape Machine Intelligence!
  Book Description
  This book takes you through a step-by-step learning journey, starting with the essentials of Julia's syntax, variables, and functions. You'll unlock the power of efficient data handling by leveraging Julia arrays and DataFrames.jl for insightful analysis. Develop expertise in both basic and advanced statistical models, providing a robust toolkit for deriving meaningful data-driven insights. The journey continues with machine learning proficiency, where you'll implement algorithms confidently using MLJ.jl and MLBase.jl, paving the way for advanced data-driven solutions. Explore the realm of Bayesian inference skills through practical applications using Turing.jl, enhancing your ability to extract valuable insights. The book also introduces crucial Julia packages such as Plots.jl for visualizing data and results.
  The handbook culminates in optimizing workflows with Julia's parallel and distributed computing capabilities, ensuring efficient and scalable data processing using Distributions.jl, Distributed.jl and SharedArrays.jl. This comprehensive guide equips you with the knowledge and practical insights needed to excel in the dynamic field of data science and machine learning.
  Table of Contents
  1. Julia In Data Science Arena
  2. Getting Started with Julia
  3. Features Assisting Scaling ML Projects
  4. Data Structures in Julia
  5. Working With Datasets In Julia
  6. Basics of Statistics
  7. Probability Data Distributions
  8. Framing Data in Julia
  9. Working on Data in DataFrames
  10. Visualizing Data in Julia
  11. Introducing Machine Learning in Julia
  12. Data and Models
  13. Bayesian Statistics and Modeling
  14. Parallel Computation in Julia
  15. Distributed Computation in Julia
  Index

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  Denver the (not so) Great

  B. E. Baker

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  A compelling story of one family's determination to save their grumpy old horse against all odds. 
  The Baker family bought Denver to be a family horse, and he took care of their children for several years as well as he could. So when, in a freak trailer accident, Denver injured himself badly, the family was upset. 
  Denver's girl, Tessa, was devastated.  
  Sadly, his injury was difficult to diagnose, and once they finally figured out what was wrong, it was so rare that it didn't really have an established treatment. The vets suggested the Bakers put him down, since he was old, and frankly, not so great. He hadn't been expnsive, and the experimental treatment they thought might save him was risky, long term, and expensive.  
  The Baker family decided to take a gamble on their beloved horse anyway.  
  The decision changed all their lives, and it blessed them in ways they never expected. Join Denver and Bridget as they tell the story from dual POVs. It will break your heart, but it will heal it again and then some.

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  Space to Grow - Unlocking the...

  Matthew Weinzierl, Brendan Rosseau

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  Space is a place of unparalleled possibility for humanity, and it's undergoing a revolution. A wave of companies led by gutsy entrepreneurs are unlocking opportunities that fire the imagination. No, it's not hotels on Mars or day trips to orbit (yet), but it's an awe-inspiring transformation driven by innovative technologies, creative approaches, hard work, and—for the first time—market forces. Above all, this revolution is uncovering the simple but unfamiliar truth that space is a place: a place where countries, markets, and each of us can play a vital role in realizing some of our biggest, boldest dreams. 
   
   
   
  But we won't succeed through dreams alone. The space economy is just that—an economy—governed by the same laws of supply and demand that apply here on Earth. The authors, who teach a highly popular course on the topic at Harvard Business School, bring the revolution in space to life through players you know—like SpaceX and Blue Origin—and many you may not, like Astroscale, founded by a Japanese IT executive who quit his job to start a company to clean up space debris. They also bring to bear fundamental tools from economics to understand how the market in space is forming, how it's fast becoming a source of value for businesses across industries and for society as a whole, and how we can best ensure that its growth benefits us all.

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  Mastering Time Series Analysis...

  Sulekha Aloorravi

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  Decode the language of time with Python. Discover powerful techniques to analyze, forecast, and innovate.
  Book Description
  "Mastering Time Series Analysis and Forecasting with Python" is an essential handbook tailored for those seeking to harness the power of time series data in their work.The book begins with foundational concepts and seamlessly guides readers through Python libraries such as Pandas, NumPy, and Plotly for effective data manipulation, visualization, and exploration. Offering pragmatic insights, it enables adept visualization, pattern recognition, and anomaly detection.
  
  Advanced discussions cover feature engineering and a spectrum of forecasting methodologies, including machine learning and deep learning techniques such as ARIMA, LSTM, and CNN. Additionally, the book covers multivariate and multiple time series forecasting, providing readers with a comprehensive understanding of advanced modeling techniques and their applications across diverse domains.Readers develop expertise in crafting precise predictive models and addressing real-world complexities. Complete with illustrative examples, code snippets, and hands-on exercises, this manual empowers readers to excel, make informed decisions, and derive optimal value from time series data.
  
  Table of Contents
  1. Introduction to Time Series
  2. Overview of Time Series Libraries in Python
  3. Visualization of Time Series Data
  4. Exploratory Analysis of Time Series Data
  5. Feature Engineering on Time Series
  6. Time Series Forecasting – ML Approach Part 1
  7. Time Series Forecasting – ML Approach Part 2
  8. Time Series Forecasting - DL Approach
  9. Multivariate Time Series, Metrics, and Validation      
  Index

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  Hindsight - In Search of Lost...

  Jenna Watt

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  "Essential reading for lovers of the Great outdoors" —Roger Cox, Scotsman magazine 
   
   
   
  Longlisted for the 2022 Highland Book Prize 
   
   
   
  In 2019, Jenna Watt took part in the stalking of a hind on the vast Highland estate of Corrour: part of an immersive attempt to understand the ideas that lie behind 'rewilding', and what it means emotionally and physically to participate in Scotland's deer cull. Piece by piece and chapter by chapter she unravels the story of that one day spent hunting the hind, interlaced with her discovery that her ancestors were deer stalkers, game keepers, and ghillies on a Highland estate, who once took part in increasingly controversial land practices like muirburn and species persecution. 
   
   
   
  This exploration leads her into the complex and often conflict-ridden world of the rewilding movement. 
   
   
   
  In the process, Jenna comes to better understand the meaning of 'wildness', the shifting baselines of 'rewilding', and, in a world beset by climate change and species extinction, how to cope, both as an individual and as a society, with the concept of ecological grief.

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