188 - Hyperparameter tuning for activation function, optimizer and weight initialization
Code generated in the video can be downloaded from here:
https://github.com/bnsreenu/python_for_microscopists
Видео 188 - Hyperparameter tuning for activation function, optimizer and weight initialization канала DigitalSreeni
https://github.com/bnsreenu/python_for_microscopists
Видео 188 - Hyperparameter tuning for activation function, optimizer and weight initialization канала DigitalSreeni
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
170 - AutoKeras for structured data classification using the Wisconsin breast cancer data set83 - Running your Docker in the cloudPython tips and tricks - 3: Be conservative with image augmentationExtracting a Targeted Subset from a COCO JSON annotated datasetDigital Sreeni Channel name change from Python for Microscopists233 - Semantic Segmentation of BraTS2020 - Part 2 - Defining your custom data generator84 - How to build a Docker (module) with your code and run it on APEER?339 - Surrogate Optimization explained using simple python code308 - An introduction to language models with focus on GPT327 - An introduction to Single Molecule Fluorescence In Situ Hybridization (smFISH)Book Review - Deep Learning with fastai CookbookWhat I am reading this week about Machine Learning and AI - 13 August 2021326 - Cell type annotation for single cell RNA seq data65 - Image Segmentation using traditional machine learning - Part3 Feature Ranking39 - Introduction to Pandas - Grouping DataAMT1 - Extracting required information from your Outlook inbox320 - Understanding Simulated Annealing using steel optimization335 - Converting COCO JSON annotations to labeled mask images108 - Analysis of COVID-19 data using Python - Part 266 - Image Segmentation using traditional machine learning - Part4 Pickling Model151 Warning about JPG files when working with categorical labels