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- Level: Beginner
- Duration: 04h 21m 51s
- Release date: 2022-02-14
- Author: Google Cloud
- Provider: Pluralsight
Managing Machine Learning Projects with Google Cloud
Description
Content
Business professionals in non-technical roles have a unique opportunity to lead or influence machine learning projects.
- Introduction05m
- Introduction05m
- Identifying business value for using ML26m
- Introduction04m
- AI vs ML vs Deep Learning11m
- Phase 1: Assess feasibility04m
- Practice assessing the feasibility of ML use cases07m
- Module 2: Worksheet00m
- Defining ML as a practice42m
- Common ML problem types09m
- Standard algorithm and data04m
- Data quality09m
- Predictive insights and decisions05m
- More ML examples06m
- Practice series: Analyze the ML use case01m
- Module 3: Worksheet00m
- Saving the world's bees01m
- Google Assistant for accessibility02m
- Exercise review and Why ML now05m
- Building and evaluating ML models54m
- Features and labels07m
- Building labeled datasets18m
- Training an ML model21m
- General best practices03m
- Introduction to hands-on labs05m
- Lab: Identifying damaged car parts with AutoML Vision00m
- Lab 1: Review00m
- Using ML responsibly and ethically32m
- Human bias in ML02m
- Google's AI Principles05m
- Common types of human bias06m
- Evaluating model fairness12m
- Guidelines and Hands-on Lab06m
- Lab: Inspecting a Dataset for Bias using TensorFlow Data Validation and Facets Overview00m
- Lab 2: Review01m
- Discovering ML use cases in day-to-day business45m
- Replacing rule-based systems with ML08m
- Automate processes and understand unstructured data09m
- Personalize applications with ML11m
- Creative uses of ML13m
- Sentiment analysis and Hands-on Lab02m
- Lab: Sentiment Analysis with Natural Language API00m
- Lab 3: Review02m
- Managing ML projects successfully49m
- Key consideration 1: business value06m
- Data strategy (pillars 1–3)08m
- Data strategy (pillars 4–7)07m
- Data governance09m
- Build successful ML teams08m
- Create a culture of innovation and Hands-on Lab09m
- Lab: Evaluate an ML model with BigQuery ML00m
- Lab 4: Review02m
- Summary08m
- Summary08m
- Course Resources00m
- Course Resources00m
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