I Built a Neural Network from Scratch
Neural networks have been gaining popularity in recent years, thanks to their ability to learn complex patterns and make predictions based on data. I was fascinated by the concept of neural networks and decided to build one from scratch to understand how they work at a fundamental level.
Building the Neural Network
Building a neural network involves several key components, including the input layer, hidden layers, and output layer. I started by defining the structure of the neural network, including the number of nodes in each layer and the activation function to use.
Next, I implemented the forward and backward propagation algorithms, which allow the neural network to learn from the input data and make predictions. I trained the neural network on a dataset and fine-tuned the weights and biases to minimize the error between the predicted output and the actual output.
Evaluating the Neural Network
After training the neural network, I evaluated its performance on a separate test dataset to assess its accuracy and generalization capabilities. I also experimented with different hyperparameters and network architectures to optimize the neural network’s performance.
Overall, building a neural network from scratch was a challenging but rewarding experience. It gave me a deep understanding of how neural networks work and the mathematics behind them. I now have the skills to design and implement neural networks for various applications, from image recognition to natural language processing.
Conclusion
Building a neural network from scratch is a valuable learning experience for anyone interested in machine learning and artificial intelligence. It provides a hands-on opportunity to understand the inner workings of neural networks and how they can be applied to solve real-world problems.
If you’re interested in delving deeper into the world of neural networks, I highly recommend trying to build one from scratch. It’s a challenging but enlightening journey that will expand your knowledge and skills in this exciting field.
I'm not an AI expert by any means, I probably have made some mistakes. So I apologise in advance 🙂
Also, I only used PyTorch to test the forward pass. Apart from that, everything else is written in pure Python (+ use of Numpy).
Do it in c++
Now do it in assembly
Cool do it in assembly level language now
…..sir, this is Wendy's
Nice video, btw do you do live coding session ? Like on twitch or here on yt
Hello @Green code how did you did that…
I am beginner in machine learning studying numpy, pandas and matplotlib
How did you did that. I am also interested in data science but i am not finding exact path..
Please guide bro
trying to explain machine learning without too much maths is like trying to explain a steak without knowing what meat is. amazing job dude, incredible simple explanation
Amazing video
Nice, 17k sub
Now do it in Minecraft. Oh, it has already been done by matbatwings
Urge to create my own neural network 😫😫😫
Awesome bro. Waiting for more videos like this.
yk what … now im dead … cause i took cse with AI and ML 💀💀💀💀💀💀
Now i understood what my AI lecturer trying to say in his class😢
Its no way near doing it from scratch. Do it in C or some other low level language. Even reading the binary dataset is pain in the ass.
It is simple but where is source code 🙄🙄🙄🙄
*Who understand it
I FOUND CODE BULLLETS SON!!!!!
Great work bro! u got another subscriber !!
What a great vid, new sub
You summarize accurately two weeks of class of a ML Master where I didn't slept
Great job doing that and understanding the fundamentals
Ignore bad comments
Keep the pace