List: Neural Networks and Deep Learning Course | Curated by Rukshan Pramoditha

Dec 22, 2023
55 stories
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Neural Networks and Deep Learning CourseLearn from the basics with a hands-on approach by using Python, NumPy, TensorFlow and Keras. So, everyone can understand!
Part 50
Rukshan Pramoditha
The Intuition behind the Universal Approximation Theorem for Neural NetworksCan neural networks approximate any non-linear function?
Dec 21, 2023
2
Dec 21, 2023
2
Part 49
Rukshan Pramoditha
Multi-Fedlity Optimization for Hyperparameter Tuning in Multi-Layer Perceptrons (MLPs)Utilizing Coarse-to-Fine Search (CFS) for an informed search of best neural network hyperparameters
Aug 5, 2023
Aug 5, 2023
Part 48
Rukshan Pramoditha
Autoencoders vs t-SNE for Dimensionality ReductionWhile preserving spatial relationships between data points in both lower and higher dimensions
Jun 30, 2023
1
Jun 30, 2023
1
Part 47
Rukshan Pramoditha
Generating Flower Images Using Deep Convolutional GANsImplementation of CNN-based GANs (DCGANs) with Keras to generate natural-looking, realistic flower images
Apr 13, 2023
1
Apr 13, 2023
1
Part 46
In
Data Science 365
by
Rukshan Pramoditha
Using Inbuilt Datasets with TensorFlow Datasets (TFDS)Take advantage of ready-to-use datasets with TensorFlow for your ML and DL tasks
Mar 26, 2023
Mar 26, 2023
Part 45
In
Towards Data Science
by
Rukshan Pramoditha
PCA vs Autoencoders for a Small Dataset in Dimensionality ReductionNeural Networks and Deep Learning Course: Part 45
Feb 16, 2023
1
Feb 16, 2023
1
Part 44
In
Towards Data Science
by
Rukshan Pramoditha
Convolutional vs Feedforward Autoencoders for Image DenoisingCleaning corrupted images using convolutional and feedforward autoencoders
Jan 24, 2023
1
Jan 24, 2023
1
Part 43
In
Data Science 365
by
Rukshan Pramoditha
Altering the Sampling Distribution of the Training Dataset to Improve Neural Network’s Accuracy3 Methods you should know in 2023
Dec 7, 2022
Dec 7, 2022
Part 42
In
Data Science 365
by
Rukshan Pramoditha
A Short Introduction to GANs in Generative Deep LearningThe battle between two adversaries
Dec 3, 2022
1
Dec 3, 2022
1
Part 41
In
Data Science 365
by
Rukshan Pramoditha
Deep Learning Hardware Selection Guide for 2023To run deep learning models incredibly faster
Oct 31, 2022
Oct 31, 2022
Part 40
In
Data Science 365
by
Rukshan Pramoditha
Learning Rate Schedules and Decay in Keras OptimizersOptions for changing the learning rate during training
Oct 5, 2022
Oct 5, 2022
Part 39
In
Data Science 365
by
Rukshan Pramoditha
Plotting the Learning Curve to Analyze the Training Performance of a Neural NetworkTo detect overfitting and underfitting as well as slow convergence, oscillating, oscillating with divergence
Sep 29, 2022
Sep 29, 2022
Part 36
In
Towards Data Science
by
Rukshan Pramoditha
Classification of Neural Network HyperparametersBy network structure, learning and optimization, and regularization effect
Sep 16, 2022
Sep 16, 2022
Part 35
In
Data Science 365
by
Rukshan Pramoditha
How the Dimension of Autoencoder Latent Vector Affects the Quality of Latent RepresentationHyperparameter tuning in autoencoders — Part 2
Sep 8, 2022
Sep 8, 2022
Part 37
In
Towards Data Science
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
Part 38
In
Data Science 365
by
Rukshan Pramoditha
Determining the Right Batch Size for a Neural Network to Get Better and Faster ResultsGuidelines for choosing the right batch size to maintain optimal training speed and accuracy while saving computer resources
Sep 26, 2022
Sep 26, 2022
Part 33
In
Data Science 365
by
Rukshan Pramoditha
Batch Normalization Explained in Plain EnglishTheory and implementation in Keras
Aug 30, 2022
Aug 30, 2022
Part 32
In
Data Science 365
by
Rukshan Pramoditha
All You Need to Know about Batch Size, Epochs and Training Steps in a Neural NetworkAnd the connection between them explained in plain English with examples
Aug 26, 2022
2
Aug 26, 2022
2
Part 31
In
Towards Data Science
by
Rukshan Pramoditha
How Number of Hidden Layers Affects the Quality of Autoencoder Latent RepresentationHyperparameter tuning in autoencoders — Part 1
Aug 23, 2022
Aug 23, 2022
Part 34
In
Data Science 365
by
Rukshan Pramoditha
How covariate shift happens in neural networksAnd eliminating it with batch normalization
Sep 3, 2022
Sep 3, 2022