Content-Based Recommendations - Recommender Systems Part 1 скачать в хорошем качестве

Content-Based Recommendations - Recommender Systems Part 1

In this video, we break down how content-based recommender systems work, using a simple book recommendation example. You'll learn how user preferences and item features interact to predict ratings, setting the foundation for a full mini-series on building effective recommender systems. Related Videos ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Overfitting vs Underfitting:    • Overfitting vs Underfitting - Explained   Why Models Overfit and Underfit - The Bias Variance Trade-off:    • Bias-Variance Trade-off - Explained   Least Squares vs Maximum Likelihood:    • Least Squares vs Maximum Likelihood   Why We Don't Use the Mean Squared Error (MSE) Loss in Classification:    • Why We Don't Use the Mean Squared Error (M...   Hyperparameters Tuning: Grid Search vs Random Search:    • Hyperparameters Tuning: Grid Search vs Ran...   XGBoost Explained in Under 3 Minutes:    • XGBoost Explained in Under 3 Minutes   Contents ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 00:00 - Intro 01:01 - Content-based recommendation 01:31 - Inference 02:21 - Training 03:06 - Outro Follow Me ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 🐦 Twitter: @datamlistic   / datamlistic   📸 Instagram: @datamlistic   / datamlistic   📱 TikTok: @datamlistic   / datamlistic   Channel Support ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ The best way to support the channel is to share the content. ;) If you'd like to also support the channel financially, donating the price of a coffee is always warmly welcomed! (completely optional and voluntary) ► Patreon:   / datamlistic   ► Bitcoin (BTC): 3C6Pkzyb5CjAUYrJxmpCaaNPVRgRVxxyTq ► Ethereum (ETH): 0x9Ac4eB94386C3e02b96599C05B7a8C71773c9281 ► Cardano (ADA): addr1v95rfxlslfzkvd8sr3exkh7st4qmgj4ywf5zcaxgqgdyunsj5juw5 ► Tether (USDT): 0xeC261d9b2EE4B6997a6a424067af165BAA4afE1a #recommendersystems #machinelearning #ai #contentbasedfiltering #datascience