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Top June Stories: How Much Math do you need in Data Science? Easy Speech-to-Text with Python

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Top June Stories: How Much Math do you need in Data Science? Easy Speech-to-Text with Python

Also: Deep Neural Networks and the Jennifer Aniston Neuron; Don’t Democratize Data Science.


Here are the most popular posts in KDnuggets in June.

Platinum BlogMost Viewed – Platinum Badge (>20,000 UPV)

  1. How Much Math do you need in Data Science?, by Benjamin Obi Tayo (*)
  2. Easy Speech-to-Text with Python, by Dhilip Subramanian (*)

Gold BlogMost Viewed – Gold Badge (>10,000 UPV)

  1. Learning by Forgetting: Deep Neural Networks and the Jennifer Aniston Neuron, by Jesus Rodriguez (*)
  2. Don’t Democratize Data Science, by Rahul Agrawal
  3. If you had to start statistics all over again, where would you start?, by Lee Baker (*)

Silver BlogMost Viewed – Silver Badgs (> 5,000 UPV)

  1. Deep Learning for Coders with fastai and PyTorch: The Free eBook, by Matthew Mayo
  2. 4 Free Math Courses to do and Level up your Data Science Skills, by Gonzalo Ferreiro Volpi
  3. Naive Bayes Algorithm: Everything you need to know, by Nagesh Singh Chauhan
  4. The Most Important Fundamentals of PyTorch you Should Know, by Kevin Vu
  5. Overview of data distributions, by Madalina Ciortan (*)
  6. A Complete guide to Google Colab for Deep Learning, by Ahmad Anis
  7. From Languages to Information: Another Great NLP Course from Stanford, by Matthew Mayo (*)

Platinum BlogMost Shared – Platinum Badge (>1000 UPV)

  1. How Much Math do you need in Data Science?, by Benjamin Obi Tayo (*)

Gold BlogMost Shared – Gold Badge (>500 shares)

  1. Deep Learning for Coders with fastai and PyTorch: The Free eBook, by Matthew Mayo
  2. A Complete guide to Google Colab for Deep Learning, by Ahmad Anis

Silver BlogMost Shared – Silver Badge (>250 shares)

  1. 4 Free Math Courses to do and Level up your Data Science Skills, by Gonzalo Ferreiro Volpi
  2. Easy Speech-to-Text with Python, by Dhilip Subramanian
  3. Natural Language Processing with Python: The Free eBook, by Matthew Mayo
  4. Deep Learning for Detecting Pneumonia from X-ray Images, by Abhinav Sagar
  5. Uber’s Ludwig is an Open Source Framework for Low-Code Machine Learning, by Jesus Rodriguez
  6. From Languages to Information: Another Great NLP Course from Stanford, by Matthew Mayo
  7. Overview of data distributions, by Madalina Ciortan
  8. Understanding Machine Learning: The Free eBook, by Matthew Mayo (*)
  9. Skills to Build for Data Engineering, by Mohammed M Jubapu (*)
  10. Naive Bayes Algorithm: Everything you need to know, by Nagesh Singh Chauhan
  11. Five Cognitive Biases In Data Science (And how to avoid them), by Rahul Agrawal (*)

(*) indicates that badge added or upgraded based on these monthly results.

Most Shareable (Viral) Blogs

Among the top blogs, here are the blogs with the highest ratio of shares/unique views, which suggests that people who read it really liked it.

  1. Uber’s Ludwig is an Open Source Framework for Low-Code Machine Learning, by Jesus Rodriguez
  2. Skills to Build for Data Engineering, by Mohammed M Jubapu
  3. A Complete guide to Google Colab for Deep Learning, by Ahmad Anis
  4. Deep Learning for Detecting Pneumonia from X-ray Images, by Abhinav Sagar
  5. Introduction to Pandas for Data Science, by Ahmad Anis
  6. Deep Learning for Coders with fastai and PyTorch: The Free eBook, by Matthew Mayo

Source: https://www.kdnuggets.com/2020/07/top-stories-2020-jun.html

Big Data

Best Apps to Check Internet Speed

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Currently, there are approximately 4.57 billion active internet users in the world. With such a large number of people accessing the internet at the same time, it is fair enough that your internet speed slows down sometimes. If at any time you feel like your internet is acting slower than usual, you can take a seed test to find out whether you are getting promised speeds or not.

What Is A Speed Test?

A speed test evaluates the quality of your internet connection. It measures upload data rate, latency rate, download speed, and other related parameters.

If you want to check your data speed, then turn your Wi-Fi off before running the test. To help you accurately check your data and internet speed anytime, this blog guides you about the best speed testing apps for web, iOS, macOS, Android, Apple TV, Google Chrome, and iPhone. So, let’s dig in!

Ookla Speedtest

This is the most authentic method to check your network diagnostics and internet speeds. More than 10 million people use this site on a daily basis. It displays your upload and download speed in Mbps within a few seconds. Ookla is undoubtedly one of the highly trusted apps that also provide you details about your provider and server.

If you want to track your internet speed in a specific area, then you can create an account on the app and monitor your internet speed during different intervals in the same area.

Availability

All iOS, web, macOS, Google Chrome, Android, Apple TV, and Windows users can access the Ookla Speedtest app for free.

SpeedSmart

Another famous internet speed test app is the SpeedSmart developed by Speedtest.net. Its accuracy level is one of the best as it uses HTML5 rather than Java or Flash. This utilization also makes this app work faster. The app has a user-friendly interface, and it also allows you to check your internet speed anytime and compare it with previous speed results automatically saved in the app’s result history.

Availability

SpeedSmart app is available globally to iOS, web, and Android users.

V-SPEED Speed Test

A customizable internet speed testing app, V-Speed’s cloud-managed test allows you to execute advanced VoIP tests, check statistics database, calculate bandwidth, and much more.

Availability

The V-Speed app is available for download to both iPhone and Android users.

Bandwidth Place

Bandwidth Place offers a speed test for all devices regardless of the location. If you have a good connection like Windstream internet service, then you can use any device to access this site and check your upload and download speeds.

Availability

This app is available on any device that has an internet connection.

Speedtest Master

This is probably the fastest internet speed testing app that gives accurate results in just 30 seconds. You may have ADSL, DSL, Wi-Fi, 5G, 4G, 3G, or 2G, Speedtest Master gives accurate results in just one tap.

Availability

Speedtest Master is only available to iPhone users.

Speedcheck Internet Speed Test

A speed testing app that instantly checks your internet speed and also performs troubleshoot to improve your slow internet speed. The best thing about this site is that it guides you on how you can interpret the results of your speed test.

Availability

Speedcheck Internet speed test is available for web, Android, and iPhone users.

FAST

Developed by Netflix, Fast offers you seamless streaming. It makes sure that your device is capable to smoothly run your favorite show. Apart from showing upload speed, download speed, current location, and latency, this app also gives information about your ISP’s server location.

Availability

You can access this app from the web, iPhone, and Android devices.

Meteor Speed Tester

Meteor not only checks your internet speed but also allows you to evaluate Twitter, Facebook, and other sites to ensure everything is running smoothly before publishing something online.

Availability

The app is available for only iPhone and Android users.

Bottom Line

We would recommend you to always use a reliable speed testing app to check your broadband and Wi-Fi speeds. It assists you in learning about your system demands, suitable download time, your internet carrier capabilities compared to other players in the market, and much more. So, what are you waiting for? Test your carrier’s performance against the internet speed of giant players like Windstream and try to stay on the network with the highest speed.

 

Source.: Nathan Jones works as the content editor at BuyTVInternetPhone. He have seven years of experience as content marketer. He writes about internet, business, app and technology.

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Big Data

How to Scrape a Website With Python

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Data collection and evaluation help you improve business processes and understand your customers. Both startups and established brands leverage data about their customer’s needs, habits, and buying preferences. Moreover, data is necessary to keep an eye on your competitor’s business strategy and pricing models.

You can easily collect data from websites, but there is no option to download the data automatically. You have two ways to accomplish this task:

First, manually copy the required data by visiting every URL and pasting the copied data on your local files. This is a time-taking and hectic job.

The second is by using a web scraping program. Scraping automates the process of copy-pasting and saves tons of time.

Hence, the second method of web scraping is one of the best ways to collect data. In this article, we will understand the process of web scraping and learn to use a powerful programming language like Python to scrape the web.

Let’s begin. 👇

 

What is web scraping?

Web scraping is a data extraction technique that uses a scraping program and a proxy server to copy large volumes of data from different URLs and store them as a local file in your computer or as cloud storage online.

You can use scraping software to extract product details from eCommerce sites, or contact details like name, address, email ids, or phone numbers from business directories. The scraping software will help you to extract data according to your business needs.

 

What is Python?

Python is a versatile and most-loved programming language that is commonly used for web scraping. The syntax is simple and easy to learn. Also, the cost of program maintenance is lower. It has several modules and packages that let you do more with less code.

 

Why is Python suitable for web scraping?

Python is a high-level and interpreted programming language best for web scraping because it handles all the web crawling related processes smoothly. Two of the most widely used frameworks that are essential for web scraping are Scrapy and Beautiful Soup. These frameworks offer debugging tools and features for searching and modifying a parse tree for efficient large scale web scraping.

The core concepts of Python are easy to understand. You can create scraping programs even if you don’t have enough coding experience because coding is easy, and there is no need for heavy coding. The presence of useful libraries makes it easier to write programs with less code.

 

Why use a proxy for web scraping?

You should never run your scraping program without a proxy because doing so might result in an IP ban. Nowadays, websites employ mechanisms such as anti-scraping bots that stop programs from accessing the website’s contents. Hence, when you use your scraping program to access your target website’s contents, it will detect and block your IP.

Python proxy scraper is the best way to scrape the web without worrying about the IP ban. A proxy server acts as an intermediary between your computer and the target website. You can work with a pool of proxies to display a different IP address and location for every request made to the target website. A proxy mimics regular browsing activity, and the anti-scraping tools can’t detect that you are using a bot to access the website. Moreover, it will hide your IP address so that you can carry out all your scraping work anonymously.

 

Web scraping with Python

Python and Beautiful Soup library is one of the most powerful combinations for scraping on a large scale. The best part is, you get a lot of online help and how-to videos to master the basics and advanced concepts of using Python for web scraping

Here is a basic overview of how you can perform web scraping with Python:

1- Find the URL that you want to scrape:

The first step is finding the URL or a set of URLs that you wish to scrape. You can identify and prepare a list of URLs depending on your scraping needs. As a beginner, you should start with just one website and then proceed with other sites only when you can run your scraping program smoothly.

2- Inspect the Page:

The second step is web crawling, where your scraper inspects the HTML of the page to identify the data points you wish to copy. Crawling is a necessary component of web scraping. While inspection, you should find the elements of the page that has the information that you need.

3- Find the data you want to extract:

The next step is identifying the exact elements on a web page that need to be copied. You should store all the data points that have the HTML. For example, you should choose the elements of a webpage that contains the data to copy and then look at the respective HTML codes of the elements to locate the data points.

4- Write the code:

Now, you have the URLs to scrape and all the data points that contain the exact data. The next step is writing the code that can automatically extract the content in the data points. You should also specify in your program the format in which you wish to store the scraped data. There are several formats available with Python-like CSV, SQL, JSON, XML, and others.

5- Run the code and extract the data:

After you have written the code, the test runs it with just one URL to see if it’s working correctly. Once you can copy the required data from a webpage, you can run your entire program with several URLs to scrape the whole data. Before you run your program, you should use a Python proxy scraper because it will help you send a high volume of requests to the target website with the risk of your IP getting banned.

6- Store the data in the required format:

Once the program runs successfully, it will automatically store the data in your desired format in your local computer or the cloud.

Please note: Before you start running your web scraping program, make sure to read the robots.txt file of the target websites. Robots.txt file contains instructions that allow or disallow scraping. Please follow and respect the instructions in the file before you choose to scrape any website.

 

Conclusion

Scraping is essential for marketers, analysts, and data scientists because it lets you make better business decisions. Python is the most preferred language to scrape complete websites. Beautiful Soup and Scrapy are two of the most useful libraries that make the work of scraping easier for you. You only need to configure your Python proxy and run your scraping program to start copying the data. Start leveraging the power of scraping to extract meaningful data for your business and improve your profits.

 

Source: Efrat Vulfsons is a data-driven writer and freelance publicist, parallel to her soprano opera singing career. Efrat holds a B.F.A from the Jerusalem Music Academy in Opera Performance.

 

 

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AI

Cartoon: Cloud Dating

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Cartoon: Cloud Dating

New KDnuggets cartoon looks at how AI can transform love and romance.


New KDnuggets cartoon gives you a respite from the virus and politics and issues of the day, and looks at how AI can transform love and romance.

Cartoon: Cloud Dating

A Scientist:

Our AI has come up with “Dating in the cloud”. It scans your social media posts and comes up with a great profile for you, automatically inflating your resume and making you more attractive. And no need to decie who pays for the meal!”

Here are other
KDnuggets AI, Big Data, Data Science, and Machine Learning Cartoons
.

and KDnuggets posts tagged
cartoon.

See also other recent KDnuggets Cartoons:

Source: https://www.kdnuggets.com/2020/10/cartoon-cloud-dating.html

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