DataHour: Relationship of ML and Statistics - Optimizing Algorithmic Functions
DataHour: Relationship of ML and Statistics - Optimizing Algorithmic Functions
08 Feb 202413:02pm - 08 Feb 202414:02pm
DataHour: Relationship of ML and Statistics - Optimizing Algorithmic Functions
About the Event
The session will cover the foundational concepts of ML and statistics, highlighting their unique roles and intersections, a comprehensive understanding of loss functions, the backbone of machine learning algorithms, exploring various types such as Mean Squared Error, Cross-Entropy, and Hinge Loss. The speaker will also focus on the critical process of optimization in machine learning, covering essential techniques like Gradient Descent, Stochastic Gradient Descent, and more advanced strategies tailored to specific algorithms.
Further topics will include the bias-variance tradeoff, the significance of confidence intervals and hypothesis testing in model assessment, and the implications of distribution assumptions on optimization efficacy. The session will also address common challenges faced during optimization, such as convergence issues and the complexities of hyperparameter tuning.
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
Who is this DataHour for?
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
About the Speaker
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