Numpy, Scipy, Matplotlib & Pandas A-Z: Machine Learning

NumPy | SciPy | Matplotlib | Pandas | Machine Learning | Data Science | Deep Learning | Pre-Machine Learning Analysis

What you'll 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

Requirements

No specific knowledge needed

Description

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!

Overview

Section 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

Section 2: Python Numpy

Lecture 5 Numpy Creating Arrays

Lecture 6 Numpy Array Indexing

Lecture 7 Numpy Array Slicing

Lecture 8 Numpy Data Types

Lecture 9 Numpy Array Shape

Lecture 10 Numpy Array Reshaping

Section 3: NumPy Random

Lecture 11 Numpy Random Data Distribution

Lecture 12 Numpy Random Permutations

Lecture 13 Numpy Seaborn

Lecture 14 Numpy Normal Distribution

Lecture 15 Numpy Binomial Distribution

Lecture 16 Numpy Poisson Distribution

Lecture 17 Numpy Uniform Distribution

Section 4: NumPy ufunc

Lecture 18 NumPy ufunc Create

Lecture 19 NumPy ufunc Simple Arithmetic

Lecture 20 NumPy ufunc Rounding Decimals

Lecture 21 NumPy ufunc Logs

Lecture 22 NumPy ufunc Summations

Lecture 23 NumPy ufunc Products

Section 5: Python Pandas

Lecture 24 Pandas Series

Lecture 25 Pandas DataFrames

Lecture 26 Pandas Read CSV

Lecture 27 Pandas Read JSON

Lecture 28 Pandas Analyzing DataFrames

All levels of students,Anyone who want to explore the world of Python,This course is for you, if you want a great career