List: Deep Learning | Curated by Gustavo R Santos

Apr 11, 2023

10 stories

2 saves

Deep Learning
In
TDS Archive
by
Dr. Roi Yehoshua
Perceptrons: The First Neural Network ModelOverview and implementation in Python
Perceptrons are one of the earliest computational models of neural networks (NNs), and they form the
Mar 28, 2023
8
Mar 28, 2023
8
In
Analytics Vidhya
by
Adrien Borderon
Predicting Ethereum (ETH) Prices With RNN-LSTM in Keras (TensorFlow)The idea of this topic is to present a simple way for predicting future prices of Ethereum cryptocurrency using exploratory analysis and…
Oct 12, 2020
Oct 12, 2020
In
TDS Archive
by
Michael Malin
TensorFlow-GNN: An End-To-End Guide For Graph Neural NetworksHow to do graph, node, and edge predictions using your own Pandas/NetworkX datasets
Jan 16, 2023
11
Jan 16, 2023
11
In
TDS Archive
by
Rashida Nasrin Sucky
How to Define Custom Layer, Activation Function, and Loss Function in TensorFlowStep-by-step explanation and examples with complete code
Nov 10, 2022
Nov 10, 2022
In
TDS Archive
by
Analytique Bourassa
Probabilistic Machine Learning Series Post 3: Weights Uncertainty with Correlated NoiseUsing correlated dropout to quantify the uncertainty of Neural Network forecasts
Sep 15, 2022
Sep 15, 2022
In
TDS Archive
by
Javi Sánchez
Build your first CNN with TensorflowA step-by-step guide to creating your first neural network
Aug 26, 2022
Aug 26, 2022
In
TDS Archive
by
Sabrina Göllner
How to reduce training parameters in CNNs while keeping accuracy >99%Good-performing neural networks do not have to be unnecessarily large
Jul 14, 2022
2
Jul 14, 2022
2
In
TDS Archive
by
Kiprono Elijah Koech
How Does Back-Propagation Work in Neural Networks?Demonstrating how background works in Neural Networks using an example.
Jul 8, 2022
5
Jul 8, 2022
5
In
TDS Archive
by
Gabriele Orlandi
The Reasonable Effectiveness of Deep Learning for Time Series ForecastingBuilding blocks for state-of-the-art models
Jun 25, 2022
3
Jun 25, 2022
3
In
TDS Archive
by
Ritwick Roy
Neural Networks: Forward pass and BackpropagationStep-by-step explanation and example using PyTorch
Jun 14, 2022
6
Jun 14, 2022
6

Deep Learning

Perceptrons: The First Neural Network Model

Overview and implementation in Python Perceptrons are one of the earliest computational models of neural networks (NNs), and they form the

Predicting Ethereum (ETH) Prices With RNN-LSTM in Keras (TensorFlow)

The idea of this topic is to present a simple way for predicting future prices of Ethereum cryptocurrency using exploratory analysis and…

TensorFlow-GNN: An End-To-End Guide For Graph Neural Networks

How to do graph, node, and edge predictions using your own Pandas/NetworkX datasets

How to Define Custom Layer, Activation Function, and Loss Function in TensorFlow

Step-by-step explanation and examples with complete code

Probabilistic Machine Learning Series Post 3: Weights Uncertainty with Correlated Noise

Using correlated dropout to quantify the uncertainty of Neural Network forecasts

Build your first CNN with Tensorflow

A step-by-step guide to creating your first neural network

How to reduce training parameters in CNNs while keeping accuracy >99%

Good-performing neural networks do not have to be unnecessarily large

How Does Back-Propagation Work in Neural Networks?

Demonstrating how background works in Neural Networks using an example.

The Reasonable Effectiveness of Deep Learning for Time Series Forecasting

Building blocks for state-of-the-art models

Neural Networks: Forward pass and Backpropagation

Step-by-step explanation and example using PyTorch

Gustavo R Santos