List: Deep Learning | Curated by Nathan Hanks

May 3, 2023
34 stories
Deep LearningStuff related to deep learning (TF, Keras)
In
Towards AI
by
Dr. Leon Eversberg
How to Train Neural Networks With Fewer Data Using Active LearningA state-of-the-art guide to the theory and practice of deep active learning
Apr 25, 2023
3
Apr 25, 2023
3
In
Unit8 - Big Data & AI
by
Julien Herzen
Training Forecasting Models on Multiple Time Series with DartsAny quantity varying over time can be represented as a time series: sales numbers, rainfalls, stock prices, CO2 emissions, Internet clicks…
Feb 15, 2021
9
Feb 15, 2021
9
In
TDS Archive
by
Nikos Kafritsas
The Best Deep Learning Models for Time Series ForecastingEverything you need to know about Time Series and Deep Learning
Dec 20, 2021
12
Dec 20, 2021
12
In
Towards AI
by
Toluwani Aremu
Choosing a Learning Rate for DNNsDuring the application process for an AI-based company, I was given a take-home assessment that included a machine learning task. One of…
Dec 26, 2022
Dec 26, 2022
In
Towards AI
by
Reza Yazdanfar
N-HiTS: Neural Hierarchical Interpolation for Time Series ForecastingThis article describes a new architecture to solve previous models’ issues: 1. Predicting with instability 2. Computational complication by…
Jan 3, 2023
3
Jan 3, 2023
3
In
Data Science 365
by
Rukshan Pramoditha
Overview of a Neural Network’s Learning ProcessNeural Networks and Deep Learning Course: Part 8
Feb 1, 2022
3
Feb 1, 2022
3
In
TDS Archive
by
Rukshan Pramoditha
How to Choose the Optimal Learning Rate for Neural NetworksGuidelines for tuning the most important neural network hyperparameter with examples
Sep 21, 2022
Sep 21, 2022
In
Deep Learning Experiments
by
Daryl Chang
Effect of Batch Size on Neural Net Trainingco-authored with Apurva Pathak
May 25, 2020
7
May 25, 2020
7
In
TDS Archive
by
Vishal Yathish
Loss Functions and Their Use In Neural NetworksOverview of loss functions and their implementations
Aug 4, 2022
2
Aug 4, 2022
2
In
TDS Archive
by
Nikos Kafritsas
DeepAR: Mastering Time-Series Forecasting with Deep LearningAmazon’s autoregressive deep network
Nov 14, 2022
2
Nov 14, 2022
2
 This story is no longer available
Ignacio Zamanillo Herreros
LSTMs vs VAR modelsFor Multivariate Multi-step Time Series Forecasting
Nov 17, 2021
1
Nov 17, 2021
1
In
TDS Archive
by
Leon Sick
Paper explained: Masked Autoencoders Are Scalable Vision LearnersHow reconstructing masked parts of an image can be beneficial
Dec 29, 2021
2
Dec 29, 2021
2
In
data from the trenches
by
Lina Faik
Deep Learning for Time Series Forecasting: Is It Worth It? (Part I)Using RNNs & DeepAR Models to Find Out
Sep 16, 2021
2
Sep 16, 2021
2
In
TDS Archive
by
Daniel Herkert
Multivariate Time Series Forecasting with Deep LearningUsing LSTM networks for time series prediction and interpreting the results
Jan 7, 2022
6
Jan 7, 2022
6
In
TDS Archive
by
Piero Paialunga
Hands on Markov Chains example, using PythonDemystifying Markov Chain one line of code at a time.
Dec 31, 2021
2
Dec 31, 2021
2
In
Analytics Vidhya
by
Dwipam Katariya
How long dependencies can LSTM & T-CNN really remember?Disclaimer: This article assumes that readers possess preliminary knowledge behind the model intuition and architecture of LSTM and CNN…
Nov 10, 2021
Nov 10, 2021
In
TDS Archive
by
Marvin Lanhenke
Build Your Neural Networks with Keras in Three WaysHow, why, and when to use each approach
Dec 16, 2021
1
Dec 16, 2021
1
In
TDS Archive
by
Michael Berk
How to Improve Deep Learning Forecasts for Time Series — Part 1The theory behind clustering and its benefits.
Oct 20, 2021
2
Oct 20, 2021
2
In
TDS Archive
by
Cory Maklin
LSTM Recurrent Neural Network Keras ExampleA step-by-by tutorial on how to perform sentiment analysis using a LSTM recurrent neural network implemented with Keras.
Jun 14, 2019
3
Jun 14, 2019
3