Challenges in Machine Learning | Problems in Machine Learning

Machine Learning or ML is one of the most successful applications of Artificial intelligence which provides systems with automated learning without being constantly programmed. It has acquired a ton of noticeable quality lately due to its capacity to be applied across scores of ventures to tackle complex issues quickly and effectively. From Digital assistants that play your music to the products being recommended based on prior search, Machine Learning has taken over many aspects of our life. It is a skill in high demand as companies require software that can grasp data and provide accurate results. The core objective is to obtain optimal functions with less confusion. But in this field, there are also many challenges and difficulties from development to production stages. The Cost of AI: https://research.google/pubs/pub43146/ ============================ Do you want to learn from me? Check my affordable mentorship program at : https://learnwith.campusx.in/s/store ============================ 📱 Grow with us: CampusX' LinkedIn: https://www.linkedin.com/company/campusx-official CampusX on Instagram for daily tips: https://www.instagram.com/campusx.official My LinkedIn: https://www.linkedin.com/in/nitish-singh-03412789 Discord: https://discord.gg/PsWu8R87Z8 Instagram: https://www.instagram.com/campusx.official E-mail us at [email protected] ✨ Hashtags✨ #100DaysOfMachineLearning #MachineLearningFullCourse #MachineLearningInHindi ⌚Time Stamps⌚ 00:00 - Intro 00:50 - Data Collection 02:22 - Insufficient Data 06:10 - Non Representative Data 09:19 - Poor Quality Data 10:32 - Irrelevant Features 13:05 - Overfitting 15:39 - Underfitting 16:33 - Software Integration 19:20 - Offline Learning/Deployment 20:45 - Cost Involved 23:20 - Outro