Welcome to Data Lit! This 3-month course is an intro to data science for beginners. In this video, I'll explain how a popular data science technique called sentiment analysis works using a real-world scenario. We'll play the role of a data scientist working at a startup making a personal healthcare device. Using sentiment analysis, we'll understand how consumers feel about a competitors product. That'll help us make decisions on how to promote our own product, and what feature we can focus on the most. Using Python, Twitter, and Google Colab, anyone can do this process in just a few minutes. Enjoy!
Code for this video:
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https://towardsdatascience.com/sentiment-analysis-with-python-part-1-5ce197074184https://www.geeksforgeeks.org/twitter-sentiment-analysis-using-python/https://www.datacamp.com/community/tutorials/simplifying-sentiment-analysis-pythonhttps://www.kaggle.com/ngyptr/python-nltk-sentiment-analysishttps://pythonspot.com/python-sentiment-analysis/https://www.analyticsvidhya.com/blog/2018/07/hands-on-sentiment-analysis-dataset-python/Join us in the Wizards Slack channel:
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https://www.wagergpt.xyzAbout the Site π
This site provides links to random videos hosted at YouTube, with the emphasis on random. π₯
Origins of the Idea π±
The original idea for this site stemmed from the need to benchmark the popularity of a video against the general population of YouTube videos. π§
Challenges Faced π€
Obtaining a large sample of videos was crucial for accurate ranking, but YouTube lacks a direct method to gather random video IDs.
Even searching for random strings on YouTube doesn't yield truly random results, complicating the process further. π
Creating Truly Random Links π οΈ
The YouTube API offers additional functions enabling the discovery of more random videos. Through inventive techniques and a touch of space-time manipulation, we've achieved a process yielding nearly 100% random links to YouTube videos.
About YouTube πΊ
YouTube, an American video-sharing website based in San Bruno, California, offers a diverse range of user-generated and corporate media content. π
Content and Users π΅
Users can upload, view, rate, share, and comment on videos, with content spanning video clips, music videos, live streams, and more.
While most content is uploaded by individuals, media corporations like CBS and the BBC also contribute. Unregistered users can watch videos, while registered users enjoy additional privileges such as uploading unlimited videos and adding comments.
Monetization and Impact π€
YouTube and creators earn revenue through Google AdSense, with most videos free to view. Premium channels and subscription services like YouTube Music and YouTube Premium offer ad-free streaming.
As of February 2017, over 400 hours of content were uploaded to YouTube every minute, with the site ranking as the second-most popular globally. By May 2019, this figure exceeded 500 hours per minute. π
List of ours generatorsβ‘
Random YouTube Videos Generator
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Random Music Video Generator
Random Pets and Animals Video Generator
Random Sports Video Generator
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