micrograd Reviews

Scikit-learn Reviews

micrograd mentions (5)

• Don't fork the code — fork the design: introducing DeepFork

  I built the first version of DeepFork to understand micrograd — Andrej Karpathy's 100-line autograd engine. Most people read micrograd for the aha moment. DeepFork turns that moment into an artifact. - Source: dev.to / about 2 months ago

• Andrej Karpathy's Neural Networks: Zero to Hero — 1) Intro to Neural Networks and Backpropagation

  Karpathy built a small project called micrograd. You can see the code here. This is made up of just a few simple lines of code, but it shows us how neural networks are built under the hood. In the video, he demonstrated how to build Micrograd and how it works step by step. - Source: dev.to / 2 months ago

• Bun ported to Rust in 6 days

  It can happen like this: - write sleek operator-overloading-based code for simple mathematical operations on your custom pet algebra - decide that you want to turn it into an autograd library [0] - realise that you now need either `RefCell` for interior mutability, or arenas to save the computation graph and local gradients - realise that `RefCell` puts borrow checks on the runtime path and can panic if you get... - Source: Hacker News / 3 months ago

• Visual Introduction to PyTorch

  Good introduction! Building pytorch-lite using python and numpy is the way to go. Free book: https://zekcrates.quarto.pub/deep-learning-library/ Ml by hand : https://github.com/workofart/ml-by-hand Micrograd: https://github.com/karpathy/micrograd. - Source: Hacker News / 6 months ago

• Porting micrograd to C++: Step One of Getting My Hands Dirty Again

  Let me be completely honest: I didn't invent anything here. This is Andrej Karpathy's brilliant micrograd ported to C++, nothing more, nothing less. But sometimes the best way to really understand something is to rebuild it in a different language, and that's exactly what I needed. - Source: dev.to / 11 months ago

Scikit-learn mentions (40)

• Detecting Ingress Tool Transfer (T1105) with Python

  Certutil.exe or notepad.exe opening an external connection lands in rare because, fleet-wide, those processes almost never egress. Tune the <= 3 threshold to your environment size. For a more principled version, score each (process, destination) pair by frequency and treat the long tail as the hunt queue, which is the same idea behind scikit-learn's rarity-based anomaly methods without the model overhead. - Source: dev.to / 2 months ago

• Best AI Cybersecurity Training for Security Teams: How to Pick

  Pre-configured environment. A working VM or container with Jupyter, pandas, scikit-learn, and transformers already installed. Realistic security datasets loaded. GTK Cyber students work in the Centaur VM, a free Apache 2.0 portable lab. If the first hour of training is fighting CUDA installs, the course is not ready. - Source: dev.to / 3 months ago

• Where to Get Hands-On AI Training for Cybersecurity Professionals

  Pre-configured environment. A good course ships a VM or container with Jupyter, pandas, scikit-learn, PyTorch or transformers, and realistic security datasets loaded. GTK Cyber students work in the Centaur VM, a free Apache 2.0 portable lab. No setup tax. - Source: dev.to / 3 months ago

• How Anomaly Detection Actually Works in Security Operations

  Isolation-based models: Build random decision trees that split features. Points that are isolated quickly (short average path length across trees) are anomalies. IsolationForest in scikit-learn implements this. Handles high-dimensional feature spaces without assuming a distribution. - Source: dev.to / 4 months ago

• Building a Personalized Meal Recommendation System

  In practice, you’ll want to use libraries (like scikit-learn or TensorFlow.js for more advanced modeling), but the principle remains: find what similar users enjoy, and use that as a basis for recommendations. - Source: dev.to / 6 months ago