Curriculum

18 Chapters · 18 Lessons

  1. 1

    Book Preview

    1. Ultimate Parallel and Distributed Computing with Julia For Data Science Free preview
  2. 2

    Introduction

    1. (Included in full purchase)

      Introduction

  3. 3

    Chapter 1 : Julia In Data Science Arena

    1. (Included in full purchase)

      Julia In Data Science Arena

  4. 4

    Chapter 2 : Getting Started with Julia

    1. (Included in full purchase)

      Getting Started with Julia

  5. 5

    Chapter 3 : Features Assisting Scaling ML Projects

    1. (Included in full purchase)

      Features Assisting Scaling ML Projects

  6. 6

    Chapter 4 : Data Structures in Julia

    1. (Included in full purchase)

      Data Structures in Julia

  7. 7

    Chapter 5 : Working With Datasets In Julia

    1. (Included in full purchase)

      Working With Datasets In Julia

  8. 8

    Chapter 6 : Basics of Statistics

    1. (Included in full purchase)

      Basics of Statistics

  9. 9

    Chapter 7 : Probability Data Distributions

    1. (Included in full purchase)

      Probability Data Distributions

  10. 10

    Chapter 8 : Framing Data in Julia

    1. (Included in full purchase)

      Framing Data in Julia

  11. 11

    Chapter 9 : Working on Data in DataFrames

    1. (Included in full purchase)

      Working on Data in DataFrames

  12. 12

    Chapter 10 : Visualizing Data in Julia

    1. (Included in full purchase)

      Visualizing Data in Julia

  13. 13

    Chapter 11 : Introducing Machine Learning in Julia

    1. (Included in full purchase)

      Introducing Machine Learning in Julia

  14. 14

    Chapter 12 : Data and Models

    1. (Included in full purchase)

      Data and Models

  15. 15

    Chapter 13 : Bayesian Statistics and Modeling

    1. (Included in full purchase)

      Bayesian Statistics and Modeling

  16. 16

    Chapter 14 : Parallel Computation in Julia

    1. (Included in full purchase)

      Parallel Computation in Julia

  17. 17

    Chapter 15 : Distributed Computation in Julia

    1. (Included in full purchase)

      Distributed Computation in Julia

  18. 18

    Index

    1. (Included in full purchase)

      Index

About the course

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.

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. Her career journey includes a stint as a Full Stack Developer at Julia Computing. Proficient in ML, DL, Computer Vision, and various frameworks, Nabanita is a dynamic professional in the research and tech domain.