Deploying Machine Learning models one pod and yml file at a time.
PS: You don't need a GPU to do ML
#Mancity 🦈
• Overly complex or full of anti-patterns
• Publicly exposing API keys
• Running GPU batch inference via pd.DataFrame.apply()
• Downloading assets with every request (instead of caching)
• Mixing business logic into UI
• Overly complex or full of anti-patterns
• Publicly exposing API keys
• Running GPU batch inference via pd.DataFrame.apply()
• Downloading assets with every request (instead of caching)
• Mixing business logic into UI
I will still recommend Andrew Ng's ML course, ISL, and a Good Software Engineering book.
Make sure you understand :
- Regression, Linear and Logistic
- Tree methods and their extension (XGBoost)
- Clustering Algorithms
- Neural Networks.
I will still recommend Andrew Ng's ML course, ISL, and a Good Software Engineering book.
Make sure you understand :
- Regression, Linear and Logistic
- Tree methods and their extension (XGBoost)
- Clustering Algorithms
- Neural Networks.
2/2
2/2