Dr. Data Science

Using sklearns GridSearchCV with Pipeline for Hyperparameter Tuning in Machine Learning

Programming for Data Science, Lec 6: Iteration (for/while loops, list comprehension, break/continue)

Machine Learning with Imbalanced Data - Part 1 (Confusion matrix, precision, and recall)

Machine Learning with Imbalanced Data - Part 5 (Ensemble learning, Bagging classifier)

Programming for Data Science, Lec 3: NumPy ndarray, np.arange, np.random, np.linalg, np.concatenate

Easiest Way to Understanding Singular Value Decomposition (SVD) with Python: numpy.linalg.svd

Visualizing Regression Models in Less Than Ten Seconds Using Seaborn

3 Easy Steps to Understand and Implement Spectral Clustering in Python

Regularization in Machine and Deep Learning (Ridge, Lasso, and Layer weight regularizers)

Understanding Vector Norms in Machine Learning (L1 and L2 norms, unit balls, and NumPy)

Dive into Deep Learning - Lecture 1: PyTorch Tensor Basics, Operations, Functions, and Broadcasting

Cross-Validation in Machine Learning: Do It Right from Scratch in Python (sklearn KFold)

The Truth About Using Data Science Methods

Functional API and hidden layers with different activation functions in Keras Deep Learning

Dive into Deep Learning Lec7: Regularization in PyTorch from Scratch (Custom Loss Function Autograd)

Understanding Pipeline in Machine Learning with Scikit-learn (sklearn pipeline)

Dive Into Deep Learning - Lecture 5: Parameter Access, Initialization, and storage in PyTorch

How to Evaluate the Performance of Clustering Algorithms in Python? (Evaluation of Clustering)

Programming for Data Science, Lec 2: Python Data Structures, List, Tuple, Set, and Dictionary

Sequential Model, Dense Layer, and Model Compile in Keras Deep Learning