100 Days of Machine Learning | CampusX - Machine Learning Development Life Cycle | MLDLC in Data Science

Machine learning has given computer systems the ability to automatically learn without being explicitly programmed. But how does a machine learning system work? So, it can be described using the life cycle of machine learning. Machine learning life cycle is a cyclic process to build an efficient machine learning project. The main purpose of the life cycle is to find a solution to the problem or project. The machine learning life cycle involves seven major steps, which are given below: 1. Gathering Data 2. Data preparation 3. Data Wrangling 4. Analise Data 5. Train the model 6. Test the model 7. Deployment ============================ 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 01:02 - Background of the Topic 01:40 - What is Software Development Life Cycle 04:40 - Framing the problem 06:00 - Gathering the Data 08:32 - Data Pre-Processing 10:25 - EDA 13:20 - Feature Engineering and Selection 15:43 - Model Training, Evaluation and Selection+ 19:23 - Model Deployment 21:23 - Beta Testing 22:45 - Optimizing the Model