Julia Programming for Machine Learning
Julia Programming for Machine Learning
Duration: 14h 43m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 4.2 GB
Genre: eLearning | Language: English
Duration: 14h 43m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 4.2 GB
Genre: eLearning | Language: English
Learn Fundamentals of Julia Programming with exploration to Data Analysis and Machine Learning : Ultimate Guide
What you'll learn
All fundamentals of Julia programming, Julia syntax for coding, DataTypes, Data-Structures in Julia.
Defining and working with Functions, Methods, Constructors, Macros in Julia programming environment.
Working with DataFrames, TimeSeries for Data Manipulation in Julia.
Date and Time objects, manipulating Period objects in Julia.
Usage of Julia packages for solving Machine Learning problems.
Usage of Data Visualization tools in Julia.
Requirements
Recapitulation of some high school mathematics and statistics.
Basic proficiency in working with computer.
Description
Welcome to this online course on Julia! This course is for anyone who wants to learn Julia programming for problem solving. Machine learning and data science are the well applied domains of Julia programming. Above all, Julia is a fast and highly efficient programming language for scientific computation. Master Julia syntax for coding through arranged topics and exercises in this course.
Full-fledged segment in this course is dedicated to know about core concept of
data manipulation
in Julia which is an essential part of data analysis.
This course includes
4 projects
on
“data analysis”
and
for building “machine learning models based on regression analysis”, to learn the usage of
Julia packages
for
data analysis
and
machine learning
.
With data manipulation and building machine learning models, we will see the usage of Julia package StatsPlots for
data visualization
.
By the end of this course, you will know how to work with Julia syntax for
writing Julia program.
working with several datatypes and data-structures.
creating and manipulating arrays.
working with raw text.
defining functions and macros.
metaprogramming.
creating objects from new datatype that can be defined in Julia.
data manipulation in DataFrame and TimeArray objects.
building machine learning models for numeric prediction.
setting up data visualization tools.
See you inside the course!
Who this course is for:
Anyone from any professional or academic background, familiar with basic high-school mathematics.
You can learn everything from scratch as a beginner programmer in this course.
If you have coding experience in any programming language (e.g., Python, R, C, C++, Fortran, COBOL, Pascal etc.), this course is for you to enhance knowledge.
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