PinnedKey Concepts In (Deep) Reinforcement LearningTo better understand RL, we need to explore some key terms such as states and observations, action spaces, policies, trajectories, etc…Jul 18, 2023Jul 18, 2023
PinnedA Comprehensive Guide to Tree-Based MethodsTree-based methods and their ensemble techniques offer powerful tools for solving a wide range of machine learning and data science…May 16, 2023May 16, 2023
Multi-Armed Bandit Problem and Its SolutionsA classic reinforcement learning problem that perfectly embodies the exploration vs exploitation dilemma.Oct 8, 2023Oct 8, 2023
Customer Segmentation using K-means Clustering in PythonHow can we effectively make sense of a massive pool of customer data?Jun 22, 2023Jun 22, 2023
Understanding Linear Regression with PythonLinear regression aims to estimate coefficients that minimize the differences between predicted and actual values of the dependent…May 23, 2023May 23, 2023
Market Basket Analysis With Apriori AlgorithmMarket Basket Analysis is a powerful data mining technique that can reveal the relationships between products and customer preferences.Apr 17, 20231Apr 17, 20231
Understanding Regularization Techniques: L1, L2 and DropoutRegularization techniques are used to prevent overfitting and improve the generalization of machine learning models.Apr 10, 2023Apr 10, 2023
Exploring Ensemble Learning: Bagging, Boosting, and StackingExplore the different ensemble learning techniques, including bagging, boosting, and stacking, and how they can be used to improve…Mar 27, 2023Mar 27, 2023
4 Hyperparameters Optimization Frameworks for Machine LearningChoosing the right hyperparameters can make or break a model’s performance.Mar 9, 2023Mar 9, 2023
