Master Deep Learning Algorithms with Extensive Math by Implementing them using TensorFlow
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Oct 2, 2020 - Jupyter Notebook
Master Deep Learning Algorithms with Extensive Math by Implementing them using TensorFlow
Hands-On Deep Learning Algorithms with Python, By Packt
Keras/TF implementation of AdamW, SGDW, NadamW, Warm Restarts, and Learning Rate multipliers
[Python] [arXiv/cs] Paper "An Overview of Gradient Descent Optimization Algorithms" by Sebastian Ruder
Gradient_descent_Complete_In_Depth_for beginners
A deep learning classification program to detect the CT-scan results using python
A news article's title and description should be classified into the following groups in order to solve this classification problem: 1-World, 2-Sports, 3-Business and 4-Science/Tech .Here is a sequence of data. This is a sequential problem, thus we may use bidirectional LSTM for classification since we have access to the data.
Analyze the performance of 7 optimizers by varying their learning rates
Фреймворк глубоко обучения на Numpy, написанный с целью изучения того, как все работает под "капотом".
Assignment submission for the course Fundamentals of Deep Learning (CS6910) in the Spring 2022 Semester, under Prof. Mitesh Khapra
Data Structures, Algorithms and Machine Learning Optimization
"Simulations for the paper 'A Review Article On Gradient Descent Optimization Algorithms' by Sebastian Roeder"
A comparison between implementations of different gradient-based optimization algorithms (Gradient Descent, Adam, Adamax, Nadam, Amsgrad). The comparison was made on some of the most common functions used for testing optimization algorithms.
This repository contains a python implementation of Feed Forward Neural Network with Backpropagation, along with the example scripts for training the network to classify images from mnist and fashion_mnist datasets from keras.
From linear regression towards neural networks...
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