scikit-learn Courses and Certifications

Codeynamics

Multiple Linear Regression with Scikit-learn in Python - Supervised Machine Learning

Master multiple linear regression techniques in Python using scikit-learn, from data preprocessing to model evaluation and prediction implementation.

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

Python Machine Learning Bootcamp

105 ratings at CreativeLive

Master Python machine learning by exploring regression, KNN, decision trees, random forests, and neural networks using real datasets like Titanic and Iris.

• CreativeLive
• 7 minutes
• Self-Paced
• Paid Course

Advanced Machine Learning Models for Prediction

3 ratings

Master advanced machine learning algorithms including SVM, decision trees, random forests, and neural networks for predictive modeling using Scikit-Learn, with focus on practical implementation and optimization.

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

Introduction to Neural Networks with TensorFlow

Master neural networks and deep learning fundamentals using TensorFlow, from data preprocessing to model training. Build and optimize architectures, implement activation functions, and enhance model performance with the Digits dataset.

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

Training Your First Machine Learning Model from Scratch

Master linear regression fundamentals by building a model from scratch using scikit-learn, covering data preparation, training, evaluation, and real-world applications with California housing data.

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

Introduction to Predictive Modeling

Gain insights into predictive modeling fundamentals using real estate data, linear regression techniques, and model evaluation methods to make data-driven decisions.

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

Career Certificate

Predictive Modeling with Python

Master predictive modeling in Python through hands-on regression analysis, data preprocessing, and advanced machine learning techniques using the California Housing Dataset.

• CodeSignal
• 13 hours
• Self-Paced
• Free Certificate
• 5 courses

Density-Based Clustering Simplified

Master density-based clustering through DBSCAN algorithm implementation, from basic concepts to advanced parameter tuning, with hands-on Python examples using scikit-learn.

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

Cluster Performance Unveiled

Master advanced clustering validation techniques using Silhouette Score, Davies-Bouldin Index, and Cross-Tabulation Analysis to optimize algorithm performance and identify ideal cluster structures.

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

Data Cleaning and Validation for Machine Learning with Python

Master data integrity, anomaly detection, and feature selection techniques to prepare clean, reliable datasets for machine learning models using Python tools.

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

Navigating Data Simplification with PCA

Master dimensionality reduction techniques using Principal Component Analysis (PCA) with Python's Scikit-learn, from basic concepts to practical implementation in machine learning projects.

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

Linear Landscapes of Dimensionality Reduction

Master dimensionality reduction techniques through Linear Discriminant Analysis (LDA), comparing it with PCA while implementing practical Python solutions for improved feature selection and model performance.

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

Dimensionality Reduction with Feature Selection

Master advanced feature selection techniques to optimize machine learning models through variance analysis, univariate selection, mutual information, and recursive elimination methods.

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

Career Certificate

Mastering Dimensionality Reduction with Python

Master Python-based dimensionality reduction techniques from PCA to autoencoders, learning to extract essential features from complex datasets and optimize machine learning model performance through hands-on practice.

• CodeSignal
• 15 hours
• Self-Paced
• Free Certificate
• 5 courses

TensorFlow Techniques for Model Optimization

Master advanced TensorFlow optimization techniques, from regularization and dropout implementation to callback utilization and Scikit-Learn integration, enhancing model performance and preventing overfitting.

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