<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>Surya's technical blog</title><link>https://blog.sdan.io/</link><description>Articles on machine learning, robotics, and software.</description><language>en</language><item><title>Teaching GPT-5 to Use a Computer</title><link>https://blog.sdan.io/teaching-gpt-5-to-use-a-computer/</link><guid>https://blog.sdan.io/teaching-gpt-5-to-use-a-computer/</guid><description>Towards self-driving computers.</description><pubDate>Tue, 12 Aug 2025 00:00:00 GMT</pubDate></item><item><title>Building a web server with Docker and Traefik Load Balancer</title><link>https://blog.sdan.io/sd2/</link><guid>https://blog.sdan.io/sd2/</guid><description>Self-host anything and everything with this simple setup</description><pubDate>Mon, 07 Oct 2019 00:00:00 GMT</pubDate></item><item><title>DAgger Explained</title><link>https://blog.sdan.io/dagger/</link><guid>https://blog.sdan.io/dagger/</guid><description>Simple overview and introduction on DAgger and its implementations</description><pubDate>Mon, 01 Apr 2019 00:00:00 GMT</pubDate></item><item><title>Policy Gradients [Draft]</title><link>https://blog.sdan.io/policy-gradients/</link><guid>https://blog.sdan.io/policy-gradients/</guid><description>Explanation, derivation, and implementation of Policy Gradients.</description><pubDate>Sun, 03 Feb 2019 00:00:00 GMT</pubDate></item><item><title>Gradients, Backprop, and Derivatives in Tensorflow [Draft]</title><link>https://blog.sdan.io/grad/</link><guid>https://blog.sdan.io/grad/</guid><description>Tutorial on computing gradients and derivatives using Numpy and Tensorflow</description><pubDate>Mon, 31 Dec 2018 00:00:00 GMT</pubDate></item><item><title>Hyperparameter Behavior in Reinforcement Learning</title><link>https://blog.sdan.io/hyperparameter/</link><guid>https://blog.sdan.io/hyperparameter/</guid><description>How do hyperparameters affect traditional RL algorithms?</description><pubDate>Sat, 29 Dec 2018 00:00:00 GMT</pubDate></item><item><title>Starting out with Numpy, Pandas, Scikit-Learn, and Keras</title><link>https://blog.sdan.io/datascience/</link><guid>https://blog.sdan.io/datascience/</guid><description>Welcome to an introductory tutorial into Data Science with Python. I will cover the basics of how to use Numpy, Pandas, Scikit-Learn, and Keras.</description><pubDate>Mon, 01 Oct 2018 00:00:00 GMT</pubDate></item><item><title>Introduction to Python</title><link>https://blog.sdan.io/python/</link><guid>https://blog.sdan.io/python/</guid><description>A simple introductory tutorial on how to use Python.</description><pubDate>Sat, 15 Sep 2018 00:00:00 GMT</pubDate></item><item><title>Building a Self Driving Car using Machine Learning</title><link>https://blog.sdan.io/iarrc2018/</link><guid>https://blog.sdan.io/iarrc2018/</guid><description>Proving Machine Learning methods can outperform traditional computationally expensive computer vision, path planning, and localization algorithms.</description><pubDate>Wed, 15 Aug 2018 00:00:00 GMT</pubDate></item></channel></rss>