Highlights from a deep learning conference covering optimization algorithms' impact on generalization and human-in-the-loop efficiency.
A practical guide to implementing a hyperparameter tuning script for machine learning models, based on real-world experience from Taboola's engineering team.
A tutorial on implementing a binary classification machine learning model using ML.NET in .NET Core to predict Titanic passenger survival.
A data science VP shares how Lazada uses machine learning for e-commerce, including automated review classification and product ranking.
A comprehensive overview of policy gradient algorithms in reinforcement learning, covering key concepts, notations, and various methods.
Exploring machine learning-driven bundling with Guess.js to optimize JavaScript chunk loading and improve SPA performance.
An introductory guide to Reinforcement Learning (RL), covering key concepts, algorithms like SARSA and Q-learning, and its role in AI breakthroughs.
Explores the Multi-Armed Bandit problem, a classic dilemma balancing exploration and exploitation in decision-making algorithms.
A web developer shares their journey learning machine learning, applying JavaScript skills to a new domain and rediscovering math.
A personal reflection on the author's achievements in 2017, including travel, starting a club, and fitness goals, with a positive outlook for 2018.
A review and tips for the OMSCS CS7641 Machine Learning course, covering assignments, exams, and workload.
A tutorial on implementing a neural network in JavaScript using Google's deeplearn.js library to improve web accessibility by choosing font colors.
A guide to implementing logistic regression with gradient descent in JavaScript to solve classification problems.
A retrospective on the transformative impact of deep learning over the past five years, covering its rise, key applications, and future potential.
Explains the Normal Equation as an alternative to Gradient Descent for linear regression in JavaScript, including implementation.
A guide to implementing multivariate linear regression with gradient descent in JavaScript, including feature scaling.
A guide to implementing vectorized gradient descent in JavaScript for machine learning, improving efficiency over unvectorized approaches.
Explores methods to optimize the gradient descent algorithm in JavaScript, focusing on selecting the right learning rate for convergence.
A recap of PyData Warsaw 2017, covering key talks, new package announcements, and analytics on the conference's international attendees.
An overview of Machine Learning applications in Remote Sensing, covering key algorithms and the typical workflow for data analysis.
