Who We Are
NeuralStack Insights is a blog by a senior AI developer based in Toronto, Canada, dedicated to sharing knowledge on neural networks, deep learning frameworks, and scalable machine learning solutions. With over 10 years of hands-on experience, our mission is to simplify complex AI technologies for developers at all levels.
BEST We Can
We cover TensorFlow, PyTorch, Keras, and other key AI tools, providing practical guides, code snippets, and detailed stack breakdowns. Whether you're a student, data scientist, or enterprise-level engineer, we’re here to help you grow in the AI era.
AI developer blog for Canadian tech professionals. Explore neural network tutorials, TensorFlow projects, and deep learning insights.
Features
Explore Canadian-made AI blog features – tutorials, tools, and weekly content on neural networks and deep learning.
Canada-Based AI Content
Get neural network guides tailored for Canadian developers .
Expert-Level Tutorials
Written by a senior AI engineer with 10+ years of industry experience.
Real Project Examples
Every tutorial is based on real-world implementation — no fluff.
Open Source Friendly
Most guides include GitHub links, so you can fork and build instantly.
Mobile-Friendly UI
Enjoy reading and coding on any device, with clean layouts and light/dark mode.
Weekly Updates
Stay updated with fresh insights every week – no outdated content.
Latest Blog Posts
Canadian AI blog with hands-on deep learning tutorials.
Building a Chatbot with TensorFlow and Keras: Step-by-Step Guide
In this tutorial, we walk you through the complete process of building a smart chatbot using TensorFlow and Keras. You'll learn how to clean and preprocess your data, train an intent classification model, and integrate your bot with a simple interface. Whether you’re creating a customer service assistant or an interactive Q&A tool, this guide provides all the foundational steps.
PyTorch vs. TensorFlow in 2025: Which AI Framework Wins?
Choosing between PyTorch and TensorFlow can be challenging. In this article, we compare the two based on performance, ease of use, documentation, and production-readiness. You’ll also find tips on which framework fits best depending on your project goals — whether it's research, deployment, or mobile AI.
How to Speed Up Neural Network Training with Mixed Precision
Training deep learning models can be time-consuming and costly. This guide introduces mixed precision training — a method that speeds up model training by using half-precision floats. You'll learn how to enable this feature with TensorFlow and PyTorch, explore benchmarks, and understand when it’s most effective. Ideal for anyone training models on GPUs.
As a junior developer diving into AI, I often felt overwhelmed by the complexity of neural networks. But this blog changed that. The tutorials are clearly written, full of practical examples, and tailored for real-world use. I managed to build my first text classification model using just one of the guides here. It’s like having a mentor online.
I’ve been working with PyTorch for three years, but I still find this blog incredibly useful. It’s rare to find content that’s both technically deep and well-explained. The performance optimization guides saved me countless hours, and the open-source tools recommended here have become part of my daily workflow.
There are so many AI blogs out there, but this one stands out. It feels focused, smart, and honest. I’ve applied techniques from the model evaluation posts directly into my research. The content respects your time and delivers real value, which is hard to find these days.
AI & Neural Network News
Discover next-gen performance tools for Canada’s growing ML ecosystem.
