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One of Oxylabs’ core beliefs is knowledge sharing. Listen to our podcast and learn more about all things web scraping. Find out why web scraping exists, discover solutions to daily challenges, and uncover what’s new in the web scraping community.
In the 6th episode of our podcast, OxyCast host Augustinas Kalvis (Software Engineer) talks to Jurijus Gorskovas (Machine Learning Engineer) about how web scraping is being revolutionized through the use of Machine Learning (ML). Jurijus shares his expertise by touching upon a multitude of ML topics, from getting a career in an ML-focused field to what features Machine Learning provides and which difficulties it solves.
In this episode, we cover the following:
Challenges of finding a job in the machine learning field
Why is machine learning an exciting field to work in?
What is a Universal E-Commerce Parser, and how does it work?
Explanation of the "feature" in machine learning
Basics of a machine learning model
Delving deeper to understand "features" even more
What problems can be solved with machine learning?
February 2, 2022
An introduction to the web scraping world
The purpose of web scraping
The process & challenges of public data gathering
Buying vs. building a web scraper
February 23, 2022
The most common challenges of web scraping
Ensuring reliability & scalability
Handling bot detection
Tips and tricks on avoiding blocks
The main principles of data parsing
Exploring the process step-by-step
Writing a good selector
Making the parser scalable
April 27, 2022
The intricacies of scaling
Boosting the number of requests
Solutions to bottlenecks
Tips on system design
The usage of proxies in web scraping
The essentials of proxies in web scraping
Considerations for proxy acquisition
The differences of proxy types
Machine Learning in web scraping
Complexities of ML in web scraping
"Features" of ML
Problem solving capabilities of ML
Our community of experts shares their experiences and discusses the limitless aspects of web scraping. Learn more about the guests of OxyCast.
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