Feature Extraction Courses and Certifications

BSidesLV

Advancing Network Threat Detection Through Standardized Feature Extraction and Dynamic Ensemble Learning

Discover how standardized feature extraction and dynamic ensemble learning achieve 97.92% accuracy in network threat detection while minimizing false positives for resilient defenses.

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

Introduction to Computer Vision

45 ratings at Coursera

Compute image features, apply 1D and 2D filters, and work with camera models and epipolar geometry by hand and in Excel using grayscale and RGB matrices.

• Coursera
• 4 weeks, 4 hours a week
• Self-Paced
• Paid Course

Edureka

Natural Language Processing Essentials

Learn NLP fundamentals: clean and tokenize text with NLTK and spaCy, extract Bag-of-Words, TF-IDF and Word2Vec features, and build named entity recognition and parsing models.

• Coursera
• 4 weeks, 3 hours a week
• Self-Paced
• Paid Course

Coursera

Transform Audio: Extract Features & Augment Models

Turn raw waveforms into ML-ready audio features with STFT, MFSCs and MFCCs, then build augmentation pipelines using noise injection and temporal and spectral transformations.

• Coursera
• 2 weeks, 1 hour a week
• Self-Paced
• Paid Course

Coursera

Preparing Multimodal Data: Vision, Audio, and NLP Pipelines

Build multimodal data pipelines: normalize images, extract optical flow and MFCC features, augment audio, and fine-tune BERT with Hugging Face and spaCy.

• Coursera
• 13 weeks, 1 hour a week
• Self-Paced
• Paid Course

Hough Transform for Image Feature Extraction - Lecture 17

Lecture on using the Hough transform to fit and detect lines and circles with rotation and scale invariance.

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

Objective-See Foundation

Mach-O Feature Extraction and Malware Similarity Analysis with YARA-X

Delve into advanced macOS malware analysis techniques, focusing on Mach-O similarity methods, YARA-X implementation, and feature extraction for improved malware detection and analysis.

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

IIT Kharagpur;  NPTEL

Pattern Recognition and Application

An analytical study of feature representation, statistical and neural recognition methods, time-varying patterns, and clustering, with applications in machine vision and speech recognition.

• Swayam
• 12 weeks
• Available until Oct 9, 2026
• Free Online Course

NPTEL;  IIT Kharagpur

Pattern Recognition and Application

This course covers feature extraction techniques and the representation of patterns in feature space. Measure of similarity between two patterns. Statistical, nonparametric and neural network techniques for pattern recognition have been discussed in this…

• YouTube
• 1 day 13 hours
• Self-Paced
• Free Video

Computer Vision - Fall 2021

Explore computer vision fundamentals from linear algebra to neural networks, covering image filtering, edge detection, CNNs, PyTorch, object detection, and segmentation techniques.

• YouTube
• 1 day 4 hours 49 minutes
• Self-Paced
• Free Video

Valerio Velardo - The Sound of AI

Mel-Frequency Cepstral Coefficients Explained Easily

Explains the cepstrum intuitively and shows how Mel-Frequency Cepstral Coefficients are extracted for speech and music processing.

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

Valerio Velardo - The Sound of AI

Extracting the Amplitude Envelope Feature From Scratch in Python

Implement an audio amplitude envelope feature from scratch in Python and compare it across music genres.

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

Valerio Velardo - The Sound of AI

How to Extract Audio Features

Learn how framing, windowing, and Fourier analysis turn audio signals into acoustic features in the time and frequency domains.

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

Valerio Velardo - The Sound of AI

Types of Audio Features for Machine Learning

Distinguish audio features by signal domain, abstraction level, temporal scope, and machine-learning approach for intelligent audio applications.

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

Wolfram

Zero to AI in 60 Minutes - Machine Learning with Wolfram Language

Master machine learning fundamentals in Wolfram Language through classification, prediction, neural networks, and deployment techniques with practical examples across diverse subjects.

• YouTube
• 1 hour 14 minutes
• Self-Paced
• Free Video