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Python for Machine Learning & Data Science Masterclass [9/2021, ENG] torrent


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Torrent added:2025-07-31 20:27:00

Download Python for Machine Learning & Data Science Masterclass [9/2021, ENG] torrent




Torrent Description
Обучающие видео » Компьютерные видеоуроки и обучающие интерактивные DVD » Machine/Deep Learning, Neural Networks

Python for Machine Learning & Data Science Masterclass

Год выпуска: 9/2021
Производитель: Udemy
Сайт производителя: https://www.udemy.com/course/python-for-machine-learning-data-science-masterclass/
Автор: Jose Portilla
Продолжительность: 44h 3m 39s
Тип раздаваемого материала: Видеоурок
Язык: Английский
Субтитры: Английский
Описание:

Learn about Data Science and Machine Learning with Python! Including Numpy, Pandas, Matplotlib, Scikit-Learn and more!
[spoiler="What you'll learn"]
You will learn how to use data science and machine learning with Python.
You will create data pipeline workflows to analyze, visualize, and gain insights from data.
You will build a portfolio of data science projects with real world data.
You will be able to analyze your own data sets and gain insights through data science.
Master critical data science skills.
Understand Machine Learning from top to bottom.
Replicate real-world situations and data reports.
Learn NumPy for numerical processing with Python.
Conduct feature engineering on real world case studies.
Learn Pandas for data manipulation with Python.
Create supervised machine learning algorithms to predict classes.
Learn Matplotlib to create fully customized data visualizations with Python.
Create regression machine learning algorithms for predicting continuous values.
Learn Seaborn to create beautiful statistical plots with Python.
Construct a modern portfolio of data science and machine learning resume projects.
Learn how to use Scikit-learn to apply powerful machine learning algorithms.
Get set-up quickly with the Anaconda data science stack environment.
Learn best practices for real-world data sets.
Understand the full product workflow for the machine learning lifecycle.
Explore how to deploy your machine learning models as interactive APIs.
[/spoiler]
Requirements Basic Python Knowledge (capable of functions) Description

This is the most complete course online for learning about Python, Data Science, and Machine Learning. Join Jose Portilla's over 3 million students to learn about the future today!

What is in the course?

Welcome to the most complete course on learning Data Science and Machine Learning on the internet! After teaching over 2 million students I've worked for over a year to put together what I believe to be the best way to go from zero to hero for data science and machine learning in Python!

This course is designed for the student who already knows some Python and is ready to dive deeper into using those Python skills for Data Science and Machine Learning. The typical starting salary for a data scientists can be over $150,000 dollars, and we've created this course to help guide students to learning a set of skills to make them extremely hirable in today's workplace environment.

We'll cover everything you need to know for the full data science and machine learning tech stack required at the world's top companies. Our students have gotten jobs at McKinsey, Facebook, Amazon, Google, Apple, Asana, and other top tech companies! We've structured the course using our experience teaching both online and in-person to deliver a clear and structured approach that will guide you through understanding not just how to use data science and machine learning libraries, but why we use them. This course is balanced between practical real world case studies and mathematical theory behind the machine learning algorithms.

We cover advanced machine learning algorithms that most other courses don't! Including advanced regularization methods and state of the art unsupervised learning methods, such as DBSCAN.
[spoiler="This comprehensive course is designed to be on par with Bootcamps that usually cost thousands of dollars and includes the following topics:"]
Programming with Python
NumPy with Python
Deep dive into Pandas for Data Analysis
Full understanding of Matplotlib Programming Library
Deep dive into seaborn for data visualizations
Machine Learning with SciKit Learn, including: Linear Regression
Regularization
Lasso Regression
Ridge Regression
Elastic Net
K Nearest Neighbors
K Means Clustering
Decision Trees
Random Forests
Natural Language Processing
Support Vector Machines
Hierarchal Clustering
DBSCAN
PCA
Model Deployment
and much, much more!
[/spoiler]
As always, we're grateful for the chance to teach you data science, machine learning, and python and hope you will join us inside the course to boost your skillset!

-Jose and Pierian Data Inc. Team

Who this course is for: Beginner Python developers curious about Machine Learning and Data Science with Python Формат видео: MP4
Видео: avc, 1280x720, 16:9, 30.000 к/с, 431 кб/с
Аудио: aac lc sbr, 44.1 кгц, 62.8 кб/с, 2 аудио
[spoiler="Изменения/Changes"]
Version 2021/1 compared to 2020/11 a total of 30 Lessons and 5 hours, it increased.

Version 2021/5 has increased by 50 lessons and about 10.5 hours compared to 2021/1.

Version 2021/9 has increased by 9 lessons (1 section) and 1 hour and 28 minutes compared to 2021/5.
[/spoiler]
[spoiler="MediaInfo"]
General
Complete name : D:\2\Udemy - Python for Machine Learning & Data Science Masterclass (9.2021)\13 - Logistic Regression\012 Logistic Regression with Scikit-Learn - Part Three - Performance Evaluation.mp4
Format : MPEG-4
Format profile : Base Media
Codec ID : isom (isom/iso2/avc1/mp41)
File size : 57.0 MiB
Duration : 15 min 56 s
Overall bit rate : 500 kb/s
Frame rate : 30.000 FPS
Movie name : 012 Logistic Regression with Scikit-Learn - Part Three - Performance Evaluation

Video
ID : 1
Format : AVC
Format/Info : Advanced Video Codec
Format profile : [email protected]
Format settings : CABAC / 4 Ref Frames
Format settings, CABAC : Yes
Format settings, Reference frames : 4 frames
Codec ID : avc1
Codec ID/Info : Advanced Video Coding
Duration : 15 min 56 s
Bit rate : 431 kb/s
Nominal bit rate : 1 600 kb/s
Width : 1 280 pixels
Height : 720 pixels
Display aspect ratio : 16:9
Frame rate mode : Constant
Frame rate : 30.000 FPS
Color space : YUV
Chroma subsampling : 4:2:0
Bit depth : 8 bits
Scan type : Progressive
Bits/(Pixel*Frame) : 0.016
Stream size : 49.1 MiB (86%)
Writing library : x264 core 148
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Codec configuration box : avcC

Audio
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Format : AAC LC SBR
Format/Info : Advanced Audio Codec Low Complexity with Spectral Band Replication
Commercial name : HE-AAC
Format settings : Explicit
Codec ID : mp4a-40-2
Duration : 15 min 56 s
Bit rate mode : Constant
Bit rate : 62.8 kb/s
Channel(s) : 2 channels
Channel layout : L R
Sampling rate : 44.1 kHz
Frame rate : 21.533 FPS (2048 SPF)
Compression mode : Lossy
Stream size : 7.16 MiB (13%)
Default : Yes
Alternate group : 1
[/spoiler]
[spoiler="Скриншоты"]

[/spoiler]

Download Python for Machine Learning & Data Science Masterclass [9/2021, ENG] torrent


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