FonePaw iPhone Data Recovery 7.6.0 | macOS | 55 mb
Professional iPhone data recovery software gives you flexible solutions to recover lost data from any iPhone, iPad and iPod running the latest iOS. Recover SMS, Contacts, Photos, Videos, Notes, Voice Memos and more by FonePaw iPhone Data Recovery.

FonePaw Android Data Recovery 5.4.0 | macOS | 43 mb
Recover deleted & lost photos, videos, audios, WhatsApp, text messages, contacts, call logs and documents from your Android devices and SD card easily.

Last updated 4/2019
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 4.11 GB | Duration: 8h 48m
Become a data visualizations expert with Python and Matplotlib 3 by learning effective data visualization recipes.

Janani Ravi | Duration: 1:43 h | Video: H264 1280x720 | Audio: AAC 44,1 kHz 2ch | 207 MB | Language: English
As working with huge numeric datasets becomes the norm, using the right tools and libraries to work with the data becomes very important. NumPy allows data analysts and data scientists to work with multi-dimensional data to solve these problems.
As machine learning and deep learning techniques become popular, getting the dataset into the right numeric form and engineering the right features to feed into ML models becomes critical.
In this course, Working with Multidimensional Data Using NumPy, you'll learn the simple and intuitive functions and classes that NumPy offers to work with data of high dimensionality.

Published 12/2022
Created by AI Sciences,AI Sciences Team
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 35 Lectures ( 2h 19m ) | Size: 955 MB

Janani Ravi | Duration: 2:08 h | Video: H264 1280x720 | Audio: AAC 44,1 kHz 2ch | 241 MB | Language: English
Matplotlib is one of the most popular visualization libraries used by data analysts and data scientists working in Python, but can often be intimidating to use. This course serves to make working with Matplotlib easy and simple.
This course will focus on making Matplotlib accessible and easily understandable to a Data Scientist or Business Analyst who needs to quickly and visually come to grips with relationships in a large dataset. In this course, Building Data Visualizations Using Matplotlib, you'll discover the basic components which make up a plot and see how you can tweak parameters and attributes to have the visualizations customized to exactly how you want it. First, you'll grow to understand the basic APIs available in Matplotlib and where they are used and learn how to customize the display, colors, and other attributes of these plots which will have multiple axes. Next, you'll build intermediate and advanced plots, drawing shapes and Bezier curves, using text and annotations to highlight plot elements, and normalizing the scales that are used on the x and y-axis. Lastly, you'll use some real-world data to visualize statistical data such as mean, median mode, and outliers, cover box plots, violin plots, histograms, pie charts, stem and stack plots and autocorrelations graphs. By the end of this course you'll not only have explored all the nitty gritty that Matplotlib has to offer; but you'll also be capable of building production-ready visuals to embed with your UI or to display within reports and presentations.
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Eassiy Android Data Recovery 5.1.6 Multilingual | 58.3 Mb
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