What I focus in this project:
- Difference between parameters and hyper-parameters.
- Different Metrics.
- Different ways of Cross Validation.
- Basic Search
- Manual Search
- Grid Search
- Random Search
- Bayesian Optimisation
- Sequential Search
- Trade-off
- Statistics
- Bayes’ Rule
- Probability reallocation
- Gaussian Distribution
- Gaussian Process
- Kernels
- Acquisition Functions
- Implementation
- Other SMBO Algorithms
- Bayesian Optimization with Random Forests (SMAC)
- Tree-structured Parzen Estimators (TPE)
- Search strategies
- Annealing with Hyperopt
- Scikit-Optimize
- Search algorithms
- objective function
- Sklearn
- Search Space
- Acquisition Function
- Analysis
- parallelization
- Implementation
- Hyperopt
- Search algorithms
- objective function
- Search Space Configuration
- nested spaces
- Acquisition Function
- Analysis: Trials
- Parallelization -MongoDB
- Implementation
- Optuna
- Search algorithms
- objective function
- Distributions
- Acquisition Function
- Search analysis
- Parallelization -SQLite
- Main setup
- Implementation
