Price: $29.22
(as of Oct 04, 2024 06:48:15 UTC – Details)
Unleash Julia’s power: Code Your Data Stories, Shape Machine Intelligence!
Key Features
● Comprehensive Learning Journey from fundamentals of Julia ML to advanced techniques.
● Immersive practical approach with real-world examples, exercises, and scenarios, ensuring immediate application of acquired knowledge.
● Delve into the unique features of Julia and unlock its true potential to excel in modern ML applications.
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.
What you will learn
● Master Julia ML Basics to gain a deep understanding of Julia’s syntax, variables, and functions.
● Efficient Data Handling with Julia arrays and DataFrames for streamlined and insightful analysis.
● Develop expertise in both basic and advanced statistical models for informed decision-making through Statistical Modeling.
● Achieve Machine Learning Proficiency by confidently implementing ML algorithms using MLJ.jl and MLBase.jl.
● Apply Bayesian Inference Skills with Turing.jl for advanced modeling techniques.
● Optimize workflows using Julia’s Parallel Processing Capabilities and Distributed Computing for efficient and scalable data processing.
Who is this book for?
This book is designed to be a comprehensive and accessible companion for anyone eager to excel in machine learning and data analysis using Julia. Whether you are a novice or an experienced practitioner, the knowledge and skills imparted within these pages will empower you to navigate the complexities of modern data science with Julia.
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
About the Author
Nabanita Dash, a results-oriented Research Engineer, holds a BTech in Computer Science and Engineering from IIIT, India. A former Head of the Programming Club, she blends technology passion with leadership. With a foundation in Mathematics, Physics, Chemistry, and English, she excels in her role as a Research Engineer at Antimodular Research in Montreal. Specializing in deep learning artworks and 2D/3D data analysis, Nabanita previously volunteered for MLPack and OpenMined, contributing to C++ data management and privacy research.
ASIN : B0CV5DK5BW
Publisher : Orange Education Pvt Ltd (January 3, 2024)
Publication date : January 3, 2024
Language : English
File size : 10076 KB
Text-to-Speech : Enabled
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Not Enabled
Print length : 688 pages
