Julia Programming For Data Science & Machine Learning: Julia

Julia Programming For Data Science & Machine Learning: Julia, available at $54.99, has an average rating of 4.2, with 37 lectures, based on 203 reviews, and has 2063 subscribers.

You will learn about update your resume with Julia Skill Learn Julia programming constructs Julia installation with Jupyter notebook Julia basics variable numbers and string Managing Third Party Package in Julia Learn different Julia collection array, dictionary and tuples & Operations Apply Julia Function for vector and matrix Operations Analyse Data with Julia Dataframes package equivalent to pandas in Python Draw plot with plots module in julia Sale Prediction using Linear Regression on Sales Data with GLM Package Predict Salary using Multiple Linear Regression on Salary Data Logistic Regression on camera data with Julia GLM Cluster Data with K-Means clustering algorithm (Clustering) Reduce Dimension of iris Dataset with PCA (MultivariateStats package) This course is ideal for individuals who are Anyone who want to learn next generation language : Julia or Anyone who want to learn fast language like c and easy language like python or Any developer who want learn Data Science with julia It is particularly useful for Anyone who want to learn next generation language : Julia or Anyone who want to learn fast language like c and easy language like python or Any developer who want learn Data Science with julia.

Enroll now: Julia Programming For Data Science & Machine Learning: Julia

Summary

Title: Julia Programming For Data Science & Machine Learning: Julia

Price: $54.99

Average Rating: 4.2

Number of Lectures: 37

Number of Published Lectures: 37

Number of Curriculum Items: 37

Number of Published Curriculum Objects: 37

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

update your resume with Julia Skill
Learn Julia programming constructs
Julia installation with Jupyter notebook
Julia basics variable numbers and string
Managing Third Party Package in Julia
Learn different Julia collection array, dictionary and tuples & Operations
Apply Julia Function for vector and matrix Operations
Analyse Data with Julia Dataframes package equivalent to pandas in Python
Draw plot with plots module in julia
Sale Prediction using Linear Regression on Sales Data with GLM Package
Predict Salary using Multiple Linear Regression on Salary Data
Logistic Regression on camera data with Julia GLM
Cluster Data with K-Means clustering algorithm (Clustering)
Reduce Dimension of iris Dataset with PCA (MultivariateStats package)

Who Should Attend

Anyone who want to learn next generation language : Julia
Anyone who want to learn fast language like c and easy language like python
Any developer who want learn Data Science with julia

Target Audiences

Anyone who want to learn next generation language : Julia
Anyone who want to learn fast language like c and easy language like python
Any developer who want learn Data Science with julia

Do you like Python, you enjoy writing python code. It’s very easy to code in python. But python is slow. So production require very high performance computing.

So we need a language which is easy to work like python and as fast as low level programming language like C.

Julia is the programming language which looks like Python and execute like C.

If you want to learn next generation fast scientific computing language and easy to work with Julia is the right solution for you and you have come at a right place to learn the Julia.

This course mainly focus on data science aspect of Julia. Although I am going to start with Julia introduction installation and major basic concepts related to Julia.

Following topics we are going to cover in this course.

Introduction to Julia and installation
Julia basics number variable send string
Julia collections, dictionary, sets and tuples.
Julia package management system and creating function in Julia
Vector and matrix related operation in Julia
Linear algebra with Julia
Data frame package
And plotting with plots package in Julia
Linear and Multiple Regression with GLM package

Udemy consider 30 days money back guarantee, so no need to worry about anything.

Get it enrolled in the course.

And I will see you inside the course.

Happy learning

Ankit mistry

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction to Julia

Lecture 2: Course – FAQ

Lecture 3: Review

Lecture 4: Installation Instruction

Lecture 5: Install Julia (Windows)

Lecture 6: Install Julia (Linux)

Lecture 7: Installation issue

Lecture 8: Getting started Julia with Jupyter Notebook

Lecture 9: Join Online Classroom

Chapter 2: Julia Code

Lecture 1: Code Download

Chapter 3: Julia Basics

Lecture 1: Numbers & Variables, Comment

Lecture 2: String

Chapter 4: Data Structure

Lecture 1: Arrays

Lecture 2: Tuples

Lecture 3: Dictionary

Lecture 4: Sets

Chapter 5: Control Flow

Lecture 1: Decision making

Lecture 2: Looping in Julia

Chapter 6: More on Julia

Lecture 1: Function

Lecture 2: Packages

Chapter 7: Vector & Matrix Processing

Lecture 1: Random package

Lecture 2: Algebra Operations

Chapter 8: Data analysis with Dataframes

Lecture 1: Getting started with DataFrames

Lecture 2: More on Dataframes

Lecture 3: Reading and Writing Dataframe

Lecture 4: Row and Column operation on DataFrames

Chapter 9: Data Visualization

Lecture 1: Getting started with Plots

Lecture 2: Some more Plots with Plots

Chapter 10: Regression

Lecture 1: Linear Regression Part – 1

Lecture 2: Linear Regression Part – 2

Lecture 3: Multiple Linear Regression

Chapter 11: Classification

Lecture 1: Logistic Regression – 1

Lecture 2: Logistic Regression – 2

Chapter 12: Clustering : Unsupervised Learning

Lecture 1: K-means Clustering – 1

Lecture 2: K-means Clustering – 2

Chapter 13: Dimensionality Reduction

Lecture 1: Princial Component analysis

Chapter 14: Bonus Lecture

Lecture 1: Discount For other course

Instructors

Ankit Mistry
Software Developer | I want to Improve your life & Income.
Data Science & Machine Learning Academy
Helping people to analyze data

Rating Distribution

1 stars: 2 votes
2 stars: 12 votes
3 stars: 37 votes
4 stars: 74 votes
5 stars: 78 votes

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