Full Scale Machine Learning with DataRobot AI Cloud Platform

End to end machine learning with DataRobot AI Cloud Platform DataRobot AI Cloud is a new approach built for the demands, challenges and opportunities of AI today. It's a single system of record, accelerating the delivery of AI to production for every organization.All users collaborate in a unified environment built for continuous optimization across the entire AI lifecycle. It is designed for the collaboration for all users in the enterprise: - Data Science & Analytics Experts - IT & DevOps Teams - Executives & Information Workers The AI Platform has 3 main functionalities: 1. Data Preparation (Make your data ready for machine learning) 2. Machine Learning (AutoML, VisualML) 3. MLOps (Deploy your model per your need) In this tutorial we are focussing on the second part of the AI platform "Machine Learning". We are going to cover in-depth details about the model building process and explain most of the functionalities related to AI cloud model training, evaluation, performance, re-training, validationm and various other steps. Video Content with Timeline: ---------------------------------------------- - (00:00) Video Start - (00:07) Video Content Intro - (02:20) AI cloud platform access - (02:30) Data Preparation Tutorial Intro - (02:59) ML Development Project - (05:21) Importing Dataset for ML - (06:02) ML Focussed EDA with source data - (07:09) Supervised ML with AI Platform - (09:44) Advance Options with ML Training - (12:19) ML Training Start - (12:48) Data Quality Exploration - (15:21) Features List in Source Data - (22:41) Features Association - (27:16) Data Quality Assessment - (29:50) AI Models in ML Project - (33:02) AI Models Repo - (37:34) Bias and Fairness - (40:49) Feature Impact and Feature Effect - (43:05) Prediction Explanations - (44:22) Explore Model Details - (44:51) Model Evaluations - (47:30) Advanced Model Tuning - (48:22) Model comparisons - (49:54) Model Speed vs Model Accuracy - (50:51) Model Insight - (51:17) Improving Model Accuracy - (53:03) Ensembling or Model Blending - (01:00:52) Deploy Model from ML Pipeline - (01:02:30) AI Report Generation - (01:03:44) AI Platform Documentation - (01:04:35) Thanks - (01:04:49) Credits Please visit: ------------------ Prodramp LLC https://prodramp.com | @prodramp https://www.linkedin.com/company/prodramp Content Creator: Avkash Chauhan (@avkashchauhan) https://www.linkedin.com/in/avkashchauhan Tags: #ai #aicloud #h2oai #driverlessai #machinelearning #cloud #mlops #model #collaboration #deeplearning #modelserving #modeldeployment #keras #tensorflow #pytorch #datarobot #datahub #aiplatform #aicloud #modelperformance #modelfit #modeleffect #modelimpact #bias #modelbias