Blogs

Machine Learning:

Ridge and Lasso Regression: L1 and L2 Regularization. Basics of regularization techniques in regression with examples. Library: Scikit-Learn.
A Simple Example of Pipeline in Machine Learning with Scikit-learn. Grid Search Cross-Validation & Sklearn Pipeline
Principal Component Analysis and SVM in a Pipeline with Python. Sklearn Pipeline, GridSerchCV and visualizing SVM decision boundary.
Interpreting Data through Visualization with Python Matplotlib. Next level interpretable data visualization. Libraries: Matplotlib & Seaborn
Opening a Restaurant in Tokyo. How to get started with a data-science project. Collecting and cleaning data to visualization + machine learning applications. Libraries: Pandas, Sklearn, Seaborn etc.

Support Vector Machines. Lagrange Multipliers & Decision Boundary Condition.
Support Vector Machines: Kernel and Mercer’s Theorem.
DBSCAN Algorithm: Complete Guide and Application with Python Scikit-Learn. Clustering spatial database and example using Canada weather station data.
Understanding Decision Tree Classification with Scikit-Learn. Gini Index, Pipeline and GridSearchCV. Understand which feature is more important and how it’s chosen.
Logistic Regression and Logits. How to think of logistic regression starting from linear Regression.

Full Review of Expectation Maximization Algorithm. ELBO, KL Divergence and Gaussian Mixture Models.
Connecting Naive Bayes & Logistic Regression.
Bayesian Neural Network: Epistemic and Aleatoric Uncertainty. What are aleatoric and epistemic uncertainties? How to include uncertainties in a neural-net model prediction?
Normalizing Flows: Getting Started and Transforming Probability Distributions. What is a normalizing flow? How do we transform between probability distributions using bijective transformations?
Masked Auto-regressive Flow: Implementing with TF-Probability. Triangular matrices are so cool!

Build Better and Faster Image Pipelines with tf.data. Why ImageDataGenerator may die soon?
Class Imbalance & Focal Loss. Application of Focal Loss using TensorFlow.
Paper Review: General and Adaptive Robust Loss Function. A loss function that can adapt during training?
Vision Transformer. What is self-attention and implementing ViT from scratch using TensorFlow 2.0

Facial Keypoints Detection: Image and Keypoints Augmentation. Inception like network and augmentation of image and keypoints using Imgaug library.
Multi-Class Classification: Cassava Leaf Disease: Case Study. Deploy a pre-trained InceptionRenset-V2 for leaf disease classification.
Chest X-ray & Pneumonia: Deep Learning with TensorFlow. Class-Imbalance, Data standardization, and AUC-ROC metric for evaluation.
Understand and Implement ResNet-50 with TensorFlow 2.0. A very deep dive to understand why residual connection is so cool and build Resnet from scratch using TensorFlow.
How Deep Neural Networks Look for Features in Images?. Visualize what’s happening in the hidden layers using TensorFlow, Keras.
Facebook Just Launched the Coolest Augmentation Library: Augly.