Valerio Velardo - The Sound of AI Courses

Batch Preprocess Audio Datasets in 1 Command

Explore praudio, a Python library for efficient audio dataset preprocessing. Learn its design, implementation, and usage for streamlining complex audio processing tasks in AI projects.

• YouTube
• 21 minutes
• Self-Paced
• Free Video

Pre-Processing Audio with Different Durations

Learn to preprocess audio data with varying lengths using PyTorch and torchaudio. Master techniques for cutting and zero-padding waveforms to standardize input for machine learning models.

• YouTube
• 21 minutes
• Self-Paced
• Free Video

Extracting Mel Spectrograms with Pytorch and Torchaudio

Master Mel Spectrogram extraction using PyTorch and torchaudio. Learn key audio transformations, resampling techniques, and practical implementation for audio processing tasks.

• YouTube
• 23 minutes
• Self-Paced
• Free Video

Implementing and Training a Neural Network with PyTorch

Build and train a feed-forward neural network using PyTorch to classify MNIST digits. Learn data management, network implementation, and training loop creation in this hands-on tutorial.

• YouTube
• 37 minutes
• Self-Paced
• Free Video

The Art of Asking Effective Questions - Tips and Strategies

Learn strategies to formulate thoughtful questions, enhancing communication skills and increasing the likelihood of receiving quality answers in professional and personal contexts.

• YouTube
• 28 minutes
• Self-Paced
• Free Video

Automatic Song Remixes With Audio Signal Processing and Simple Machine Learning

Explore Python-based Infinite Remixer for automatic song remixes using beat tracking and Nearest Neighbours search. Learn system design, usage, experiments, and potential improvements for innovative music creation.

• YouTube
• 30 minutes
• Self-Paced
• Free Video

Generating Sound Digits with a Variational Autoencoder

Learn to generate audio spectrograms of sound digits using a trained Variational Autoencoder, then convert them into audio. Includes implementation, scripting, debugging, and result evaluation.

• YouTube
• 35 minutes
• Self-Paced
• Free Video

Preprocessing Audio Datasets for Machine Learning

Build an audio preprocessing pipeline for AI in Python, covering STFT, zero-padding, and min-max normalization. Learn to batch process audio files efficiently for machine learning applications.

• YouTube
• 59 minutes
• Self-Paced
• Free Video

How to Implement a Variational Autoencoder in Python and Keras

Implement a Variational Autoencoder using Python, TensorFlow, and Keras. Learn to modify the encoder, update loss functions, train the model, and visualize the latent space for data generation.

• YouTube
• 33 minutes
• Self-Paced
• Free Video

How Is AI Revolutionising Music?

Explore how AI is transforming music creation, listening experiences, and soundtrack acquisition, revolutionizing the industry for listeners, musicians, and media creators alike.

• YouTube
• 28 minutes
• Self-Paced
• Free Video

Great AI Music Projects for Your Portfolio

Discover 7 impactful AI music projects to enhance your portfolio, showcasing skills in AI, audio processing, and coding to boost your chances of landing an AI music engineering job.

• YouTube
• 28 minutes
• Self-Paced
• Free Video

From Autoencoders to Variational Autoencoders - Improving the Encoder

Explore the transformation from autoencoders to variational autoencoders, focusing on improved encoding using multivariate normal distributions for enhanced generative capabilities in AI and sound processing.

• YouTube
• 26 minutes
• Self-Paced
• Free Video

Generation with AutoEncoders - Results and Limitations

Explore image generation using autoencoders, analyze latent space representations, and understand limitations in generative tasks. Learn why variational autoencoders are necessary for improved generation.

• YouTube
• 23 minutes
• Self-Paced
• Free Video

Building and Training an Autoencoder in Keras - TensorFlow - Python

Learn to build and train autoencoders using Python, TensorFlow, and Keras. Explore encoder-decoder architectures, implement training with the MNIST dataset, and gain practical insights into autoencoder development.

• YouTube
• 27 minutes
• Self-Paced
• Free Video

How to Implement Autoencoders in Python and Keras - The Decoder

Learn to implement the decoder component of autoencoders using Python, TensorFlow, and Keras. Covers building methods, layers, and architecture for generating sound with neural networks.

• YouTube
• 36 minutes
• Self-Paced
• Free Video