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Three Essential Hyperparameter Tuning Techniques for Better Machine Learning Models
Machine LearningLearn how to optimize your ML models for better results
7 min read -
In-Depth Support Vector Machines (SVMs) for Linear & Non-linear Classification & Regression
Artificial IntelligenceA deeper understanding of how SVMs work behind the scenes
11 min read -
Choosing the Right Number of Neighbors (k) for the K-Nearest Neighbors (KNN) Algorithm
Artificial IntelligenceSix methods to measure the effect of the number of neighbors on KNN model evaluation
13 min read -
Why is Feature Scaling Important in Machine Learning? Discussing 6 Feature Scaling Techniques
Data ScienceStandardization, Normalization, Robust Scaling, Mean Normalization, Maximum Absolute Scaling and Vector Unit Length Scaling
15 min read -
PCA vs t-SNE for visualizing high-dimensional data in a lower-dimensional space
16 min read -
Non-Negative Matrix Factorization (NMF) for Dimensionality Reduction in Image Data
Artificial IntelligenceDiscussing theory and implementation with Python and Scikit-learn
9 min read -
Performing PCA using both methods and comparing the results
8 min read -
Cleaning corrupted images using convolutional and feedforward autoencoders
10 min read -
LDA Is More Effective than PCA for Dimensionality Reduction in Classification Datasets
Artificial IntelligenceLinear discriminant analysis (LDA) for dimensionality reduction while maximizing class separability
12 min read -
Non-linear dimensionality reduction using kernel PCA
7 min read
