Many of my graduate students have papers in peer review. I share this with them to help them respond to the reviewers. I remember the challenge & pressure of writing my first papers. I sincerely hope that this helps. #AcademicChatter #academicWriting #mentorship #proflife

Howdy folks! I’m Michael Pyrcz, a proud Ukrainian-Canadian professor thrilled to be here in Texas teaching data science to students across our campus. To me, being a professor is first and foremost a role of service. That’s why I’m dedicated to sharing my educational content

This week, I had the pleasure of co-hosting a @CockrellSchool – @UT_PGE high school hackathon. One thing that stood out was how many students struggled to find the right code snippets to complete specific steps in their #DataScience and #MachineLearning workflows. To help

🚨 I recently added a brand new chapter to my free, online e-book, Applied Machine Learning in Python.📷'#DeepLearning with Autoencoders'! . This chapter includes: .1️⃣ A walkthrough of model training with all math .2️⃣ A simple autoencoder built from the ground up using NumPy

Excited to be co-hosting the @CockrellSchool High School Hackathon this week alongside Professor @johntfoster, with incredible support from our @UT_PGE department!. We’ve welcomed 56 high school students from across Texas and beyond to tackle a tough, real-world subsurface energy

Thinking about learning to code, but not quite sure?.Or maybe you know a friend or family member who’s on the fence?. To help out, I’ve put together my top reasons why every engineer and scientist should learn at least some coding!

🚨 New Chapter Alert! 🚨. I just added a brand new chapter to my free, online e-book,.Applied Machine Learning in Python — now featuring Autoencoders in #DeepLearning!. This chapter includes:.1️⃣ A walkthrough of model training with all math.2️⃣ A simple autoencoder built from the

20 miles at a good pace on my road bike at the Veloway Track in Austin, Texas. Super cool community at a wonderful place!

🧠 This morning I’m building an autoencoder by hand with only NumPy — no PyTorch, no TensorFlow. Why? .Because I believe coding it from scratch is the best way to truly understand what’s happening under the hood. 👇 Here’s what I’m doing, the full workflow:.1️⃣ Initialize weights

In response to requests from my students, I’ve built out comprehensive glossaries for my #MachineLearning and #DataAnalytics courses. It took a lot of work, but I’m absolutely stoked to share these as free resources in my open-access e-books. 📘 Data Analytics and Geostatistics

One of my former PhD students, Dr. Midé Mabadeje, and her friend Alex dropped by this morning for some #paddling and breakfast. What a treat to catch up—so much great news! I'm incredibly grateful to have had the opportunity to supervise Midé during her PhD. She was an

6 am this morning out for a paddle with Professor @johntfoster (@UT_PGE & @UTAerospace). Excellent discussion on research, data science and birds! . We saw 3 ospreys flying together with a lot of calls, possibly newly fledged juvenile(s)!

Are you attending #URTeC2025 in Houston, June 9–11?. I’ll be stepping in last minute to teach the 1-day short course “Advanced Data Analytics & Machine Learning for Energy Professionals” on Sunday, June 8. There are still plenty of seats available—join me for a hands-on day of

🎉 New Chapter Alert!. I’ve just added a brand-new chapter to my free, online e-book,. Applied Geostatistics in Python 🐍📘. Over the years, I’ve created a wide range of synthetic (fake) datasets to support students and professionals learning from my tutorials, exercises, and

🌟 New Chapter: Exploring My Synthetic Datasets. I'm working on a new chapter in my free, online e-books — a comprehensive guide to the synthetic datasets I've developed over the years. These datasets support the examples, exercises, and project work found throughout my e-books

Last week I added a new chapter on Convolutional Neural Networks (CNNs) to my FREE online e-book:. 📘 Applied Machine Learning in Python. 🌐 👉 Check it out here! ∀. I'm working hard to make #MachineLearning accessible to EVERYONE! 💥.This chapter’s got:

🎉🧠🔥 JUST DROPPED a new chapter on Convolutional Neural Networks (CNNs) in my FREE online e-book:. 📘 Applied Machine Learning in Python. 🌐 👉 Check it out here! ∀. I’m on a mission to make #MachineLearning fun, and accessible EVERYONE! 💥.This

🧠 When covering artificial neural networks in my #MachineLearning course I walk through my interactive Python dashboard, where the ANN is trained by hand — super helpful for understanding what’s really happening under the hood. 📷 Check it out on GitHub:

🌍🔥 Interested in #Spatial data, #DataAnalytics, and #Geostatistics — using Python?.Then you’ll love this! 🚀🐍📊.📘 Check out my totally FREE, 100% online e-book:.👉 ∀. 💡 What’s inside?.🎥 Links to my YouTube lectures.📊 Interactive dashboards to

If you don't impact the decision, you don't add value — I said it!. Let's make sure we know how to make decisions in the presence of uncertainty. I’ve expanded and improved the chapter on this topic in my free, online e-book, Applied Geostatistics in Python. Check it out here: