Feature Extraction Courses and Certifications

Nvidia Deep Learning Institute;  Affectiva Credential

Computer Vision

6 ratings

Master computer vision skills for robotics and automation. Analyze images, extract features, and recognize objects using deep learning. Gain expertise in object tracking, localization, and advanced applications like skin cancer detection.

• Udacity
• 37 hours
• Self-Paced
• Paid Course

Feature Engineering for Machine Learning

Master feature engineering techniques using the Abalone Dataset to improve ML model performance through extraction, selection, and transformation methods for uncovering meaningful patterns in data.

• CodeSignal
• 3 hours
• Self-Paced
• Free Certificate

Advanced Data Cleaning: Handling Text Data with Python

Master advanced text data cleaning techniques in Python, from handling mixed data types to extracting ML-ready features from messy tabular datasets.

• CodeSignal
• 1 hour
• Self-Paced
• Free Certificate

Content-Based Recommendation Systems

Dive into content-based recommendation systems, exploring factorization machines and DSSM with hands-on coding examples for developing personalized recommendation models using rich data.

• CodeSignal
• 4 hours
• Self-Paced
• Free Certificate

Navigating Data Simplification with PCA

Master dimensionality reduction techniques using Principal Component Analysis in R, from understanding eigenvectors to implementing PCA for feature extraction and classification tasks.

• CodeSignal
• 3 hours
• Self-Paced
• Free Certificate

Dimensionality Reduction with Feature Selection

Master specialized feature selection techniques to optimize machine learning models by removing low-variance features, applying correlation analysis, and using advanced methods like RFE.

• CodeSignal
• 4 hours
• Self-Paced
• Free Certificate

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 TF-IDF Vectorization in Python

1 rating

Master text vectorization techniques using TF-IDF in Python, from basic implementation to advanced parameter customization. Convert text data into numerical features and optimize for machine learning applications.

• CodeSignal
• 2 hours
• Self-Paced
• Free Certificate

Applied Machine Learning: Techniques and Applications

12 ratings at Coursera

Master applied machine learning techniques for computer vision, data analysis, and model evaluation. Gain hands-on experience with image processing, supervised learning, and essential skills in data pre-processing and performance assessment.

• Coursera
• 19 hours 24 minutes
• Self-Paced
• Paid Course

Introduction to Social Computing

Explore social computing's impact on society. Gain skills in social media analytics, responsible AI, and gamification. Apply machine learning to real-world scenarios and understand online behavior dynamics.

• Coursera
• 20 hours 45 minutes
• Self-Paced
• Paid Course

Data Science: Supervised Machine Learning in Python

3554 ratings at Udemy

Full Guide to Implementing Classic Machine Learning Algorithms in Python and with Scikit-Learn

• Udemy
• 6 hours 25 minutes
• Self-Paced
• Paid Course

Feature Engineering for Machine Learning

3492 ratings at Udemy

Learn imputation, variable encoding, discretization, feature extraction, how to work with datetime, outliers, and more.

• Udemy
• 13 hours 24 minutes
• Self-Paced
• Paid Course

Machine Learning with Apache Spark

114 ratings at Coursera

Unlock Apache Spark's potential for machine learning, covering fundamentals, supervised and unsupervised techniques, and Generative AI. Gain hands-on experience with Spark streaming, ML pipelines, and model evaluation.

• Coursera
• 15 hours 54 minutes
• Self-Paced
• Paid Course

EDUCBA

Python Case Study - Sentiment Analysis

18 ratings at Coursera

Master sentiment analysis by building a complete Python-based text classification system using NLP techniques, machine learning algorithms, and evaluation metrics.

• Coursera
• 3 hours 13 minutes
• Self-Paced
• Paid Course

Introduction to Convolutions with TensorFlow

Learn to process images using convolutions and pooling in TensorFlow, extracting key features and compressing data for improved image analysis and feature detection.

• Coursera
• 50 minutes
• Self-Paced
• Paid Course