NumPy, SciPy, Matplotlib Pandas A-Z- Machine Learning

NumPy, SciPy, Matplotlib & Pandas A-Z: Machine Learning, available at $19.99, has an average rating of 3.96, with 47 lectures, based on 192 reviews, and has 27574 subscribers.

You will learn about Solid foundation in Python programming, data types, loops, conditionals, functions and more Create and analyze projects via Python NumPy, SciPy, Matplotlib & Pandas Clean data with pandas Series and DataFrames Master data visualization Understanding the NumPy library to efficiently work with arrays, matrices, and perform mathematical operations. Go from absolute beginner to become a confident Python NumPy, Pandas and Matplotlib user This course is ideal for individuals who are All levels of students or Anyone who want to explore the world of Python or This course is for you, if you want a great career It is particularly useful for All levels of students or Anyone who want to explore the world of Python or This course is for you, if you want a great career.

Enroll now: NumPy, SciPy, Matplotlib & Pandas A-Z: Machine Learning

Summary

Title: NumPy, SciPy, Matplotlib & Pandas A-Z: Machine Learning

Price: $19.99

Average Rating: 3.96

Number of Lectures: 47

Number of Published Lectures: 47

Number of Curriculum Items: 47

Number of Published Curriculum Objects: 47

Original Price: $29.99

Quality Status: approved

Status: Live

What You Will Learn

Solid foundation in Python programming, data types, loops, conditionals, functions and more

Create and analyze projects via Python NumPy, SciPy, Matplotlib & Pandas

Clean data with pandas Series and DataFrames

Master data visualization

Understanding the NumPy library to efficiently work with arrays, matrices, and perform mathematical operations.

Go from absolute beginner to become a confident Python NumPy, Pandas and Matplotlib user

Who Should Attend

All levels of students

Anyone who want to explore the world of Python

This course is for you, if you want a great career

Target Audiences

All levels of students

Anyone who want to explore the world of Python

This course is for you, if you want a great career

Are you eager to dive into the core libraries that form the backbone of data manipulation, scientific computing, visualization, and machine learning in Python? Welcome to “NumPy, SciPy, Matplotlib & Pandas A-Z: Machine Learning,” your comprehensive guide to mastering these essential libraries for data science and machine learning.

NumPy, SciPy, Matplotlib, and Pandas are the cornerstone libraries in Python for performing data analysis, scientific computing, and visualizing data. Whether you’re a data enthusiast, aspiring data scientist, or machine learning practitioner, this course will equip you with the skills needed to harness the full potential of these libraries for your data-driven projects.

Key Learning Objectives:

Learn NumPy’s fundamentals, including arrays, array operations, and broadcasting for efficient numerical computations.

Explore SciPy’s capabilities for mathematics, statistics, optimization, and more, enhancing your scientific computing skills.

Master Pandas for data manipulation, data analysis, and transforming datasets to extract valuable insights.

Dive into Matplotlib to create stunning visualizations, including line plots, scatter plots, histograms, and more to effectively communicate data.

Understand how these libraries integrate with machine learning algorithms to preprocess, analyze, and visualize data for predictive modeling.

Apply these libraries to real-world projects, from data cleaning and exploration to building machine learning models.

Learn techniques to optimize code and make efficient use of these libraries for large datasets and complex computations.

Gain insights into best practices, tips, and tricks for maximizing your productivity while working with these libraries.

Why Choose This Course?

This course offers a deep dive into NumPy, SciPy, Matplotlib, and Pandas, ensuring you grasp their core functionalities for data science and machine learning.

Practice your skills with coding exercises, projects, and practical examples that simulate real-world data analysis scenarios.

Benefit from the guidance of experienced instructors who are passionate about data science and eager to share their knowledge.

Enroll once and enjoy lifetime access to the course materials, enabling you to learn at your own pace and revisit concepts whenever necessary.

Mastery of these libraries is crucial for anyone pursuing a career in data science, machine learning, or scientific computing.

Unlock the power of NumPy, SciPy, Matplotlib, and Pandas for data analysis and machine learning. Enroll today in “NumPy, SciPy, Matplotlib & Pandas A-Z: Machine Learning” and elevate your data science skills. Don’t miss this opportunity to become proficient in these fundamental libraries and enhance your data-driven projects!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction of Python Numpy

Lecture 2: Introduction of Numpy Random

Lecture 3: Introduction of NumPy ufunc

Lecture 4: Introduction of Pyton Pandas

Chapter 2: Python Numpy

Lecture 1: Numpy Creating Arrays

Lecture 2: Numpy Array Indexing

Lecture 3: Numpy Array Slicing

Lecture 4: Numpy Data Types

Lecture 5: Numpy Array Shape

Lecture 6: Numpy Array Reshaping

Chapter 3: NumPy Random

Lecture 1: Numpy Random Data Distribution

Lecture 2: Numpy Random Permutations

Lecture 3: Numpy Seaborn

Lecture 4: Numpy Normal Distribution

Lecture 5: Numpy Binomial Distribution

Lecture 6: Numpy Poisson Distribution

Lecture 7: Numpy Uniform Distribution

Chapter 4: NumPy ufunc

Lecture 1: NumPy ufunc Create

Lecture 2: NumPy ufunc Simple Arithmetic

Lecture 3: NumPy ufunc Rounding Decimals

Lecture 4: NumPy ufunc Logs

Lecture 5: NumPy ufunc Summations

Lecture 6: NumPy ufunc Products

Chapter 5: Python Pandas

Lecture 1: Pandas Series

Lecture 2: Pandas DataFrames

Lecture 3: Pandas Read CSV

Lecture 4: Pandas Read JSON

Lecture 5: Pandas Analyzing DataFrames

Chapter 6: Matplotlib

Lecture 1: Introduction of Matplotlib

Lecture 2: Plotting

Lecture 3: Markers

Lecture 4: Line

Lecture 5: Labels

Lecture 6: Grid

Lecture 7: Subplot

Lecture 8: Scatter

Lecture 9: Bars

Lecture 10: Histograms

Lecture 11: Pie Charts

Chapter 7: SciPy

Lecture 1: Introduction of Python SciPy

Lecture 2: SciPy Constants

Lecture 3: SciPy Optimizers

Lecture 4: SciPy Sparse Data

Lecture 5: SciPy Graphs

Lecture 6: SciPy Spatial Data

Lecture 7: SciPy Matlab Arrays

Lecture 8: SciPy Statistical Significance Tests

Instructors

Sara Academy
Programmer | Android Developer | Web Designer | Instructor

Rating Distribution

1 stars: 3 votes

2 stars: 10 votes

3 stars: 34 votes

4 stars: 80 votes

5 stars: 65 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!