I Analyzed 1000 Data Science Books on Amazon: Here’s What I Found 🤓

🔗 Deepnote 👉 📚 This Deepnote project: 🌐 The published article: @thu/Data-science-book-analysis-95de68e6-99de-4ef6-b3ae-d76602c45655 Hi data nerds! 👋 In today’s video, I’ll be walking you through a project to analyse data science books using Deepnote. I think this is a fun project to work on to both sharpen our skills on multiple levels, and to get to know more about data science books available in the market. We’ll be doing exploratory data analysis, clustering book titles to find out the common themes, and finally scraping Amazon reviews and summarising the reviews for each book. I hope you enjoy this video 😄. 🔑 TIMESTAMPS ================================ 0:00 - Intro 0:28 - Which analyses we will be doing 1:46 - Intro to Deepnote 4:41 - Dataset 5:27 - LEVEL 1 - Exploratory data analysis 8:24 - LEVEL 2 - Clustering book titles 17:19 - LEVEL 3 - Amazon review scraping & Review summarization 21:44 - Publish notebook to article and app 🙋🏻‍♀️ LET’S CONNECT! ================================ 🤓 Join my Discord server: 📩 SUBSCRIBE to my Substack to get future newsletters from me: ✍ FOLLOW me on Medium: @ (I sometimes make both video and article versions of my content, by following me on Medium you will have access to the content in writing too). 🔗 Other Links: 🔔 SUBSCRIBE to my channel (It’s FREE): COURSES & RESOURCES ================================ 💯 SQL Courses: Select Star SQL 👉 SQL tutorials 👉 📑 Excel Courses: Excel Skills for Business 👉 📊 Data Visualisation: 📚 Books I recommend: How to create effective charts and diagrams 👉 Data Viz Catalog 👉 As a member of the Amazon and Coursera Affiliate Programs, I earn a commission from qualifying purchases on the links above. By using the links you help support this channel at no cost for you. #datascience #machinelearning #DCSpaceWeek #DataAnalysis #Datanerd #ThuVu #dataanalytics