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

    Posted By: ELK1nG
    Numpy, Scipy, Matplotlib & Pandas A-Z: Machine Learning

    Numpy, Scipy, Matplotlib & Pandas A-Z: Machine Learning
    Published 11/2023
    MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
    Language: English | Size: 962.48 MB | Duration: 3h 30m

    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