Week 3 Progress - Specific Research - Neural Networks in Python

Summary/Overview:

During this weeks research I dove into several resources listed below that discussed neural networks from a Python programming perspective as well as several that discussed programming simple neural networks from a practical perspective in python. Some of these included psuedo code as well as actual coding examples. Although the actual syntax of the python coding was useful in grounding the concepts of neural networks in my previous Python experience I still struggle somewhat with some of the more advanced mathematical concepts involved in the coding process, It was useful to have a more grounded perspective however and was interesting to see just how simple the code snipets involved in creating a basic low number of layers neural network would be. I also learned more about the role kof modules in Python Neural Network coding as well as specific training datasets, where to find them and how to use them. This weeks research also helped to cement my understanding of weights in algorithms and how to compare which was one of my stumbling blocks in last weeks research.


Datasets:

There are some freely available datasets for use with training python neural networks including the TensorFlow official dataset. This dataset includes many different training datasets but the one examined in the article on Hello ML was on written numbers from 0 to 9, specifically 0s and 1s in this example. This dataset was used in the example to help to train a neural network to identify which number was written. This was a great concrete example and helped me to understand how the neural network would learn based on how the number was written in the training dataset and was then able to identify with a high level of accuracy which numbers were written in a new dataset of the same type. A sample image of some of the data is shown below.


hand written digit examples

Aditya Sharma. (2021). “A Simple Guide to Build a Neural Network from Scratch in Python”. [Diagram]. Retrieved from https://helloml.org/a-simple-guide-to-build-a-neural-network-from-scratch-in-python/


Weights:

I learned a little more about vectors and weights as they relate to neural network algorithms in Python. A very useful example was when the article on Real Python showed a graph of input vs. two weights, the visual example of the mathematical concepts of similarities helped to cement how comparing the two in a neuron in the network would help to determine the correct output. Since visually the input and weight 2 are similar it makes sense to us but in order to show this to the computer a mathematical equation is required. The graph is below.

Three vectors in a cartesian coordinate plane

Déborah Mesquita. (2021). “Python AI: How to Build a Neural Network & Make Predictions”. [Graph]. Retrieved from https://realpython.com/python-ai-neural-network/#wrapping-the-inputs-of-the-neural-network-with-numpy

 

Python Modules:

Various sources recommended importing different modules for use with Python in order to implement neural networks. Generally the purpose of this was to implement more advanced mathematical function in Python.

 

Next Steps / Future steps: 

-I will continue to refine my knowledge of python neural networks including concrete coding examples and algorithms

-I will work on researching how neural networks are used and what practical applications neural networks in Python can have.

-I will begin working on my slideshow final product teaching about what I learned about neural networks in Pytho.

 

Resources Used:

-https://www.askpython.com/python/examples/neural-networks

-https://www.springboard.com/blog/ai-machine-learning/beginners-guide-neural-network-in-python-scikit-learn-0-18/

-https://towardsdatascience.com/inroduction-to-neural-networks-in-python-7e0b422e6c24

-https://helloml.org/a-simple-guide-to-build-a-neural-network-from-scratch-in-python/

-https://towardsdatascience.com/how-to-build-your-own-neural-network-from-scratch-in-python-68998a08e4f6

-https://realpython.com/python-ai-neural-network/

-https://www.edureka.co/blog/artificial-intelligence-with-python/#Machine%20Learning%20Basics

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