If you’ve tried to learn neural networks from dense academic papers or math-heavy textbooks, you’ve probably felt overwhelmed. Enter Tariq Rashid’s Make Your Own Neural Network – a gentle, example-driven guide that promises to take you from zero to building a working neural network in Python.
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Rashid’s “puppy vs. kitten” classifier: how weights and biases adjust like learning from examples. If you’ve tried to learn neural networks from
Grab the PDF, open Jupyter Notebook, and build your first network in an afternoon. 2. Social Media Carousel (Instagram/LinkedIn – 5 slides) Slide 1 (Title): 🧠 Make Your Own Neural Network – Tariq Rashid The #1 book for coding your first NN from scratch. Today, I follow the legendary PDF Make Your
1️⃣ Design a 3-layer network (input, hidden, output). 2️⃣ Train it with backpropagation & gradient descent. 3️⃣ Test on MNIST handwritten digits.
# Query the network def query(self, inputs): hidden_inputs = np.dot(self.wih, inputs) hidden_outputs = self.activation(hidden_inputs) final_inputs = np.dot(self.who, hidden_outputs) return self.activation(final_inputs) 👉 Download the PDF legally (link in bio). 👉 Follow for more beginner-friendly AI content. 3. YouTube Video Script Outline (10 min) Title: I Built a Neural Network Without TensorFlow (Tariq Rashid Tutorial)