: Intensive coding challenge for machine learning
This project has the purpose of imporving practical skills in machine learning and artificial intelligence. After finishing the deep learning sepcialization, I decided to start coding-centered studying. The goal of this project is to make 100 notes for reading and learning from other people's code on Kaggle or Github. It'll defintely be challenging yet is expected to bring a huge growth in skills. Just like groot.
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Day Start : 23 Jan, 2019 ~ (in progress)
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Applied skills: From regression to classification, from machine learning to deep learning.
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Publication: (After finishing this challenge, planning to write and share what I learn from it)
- 92_ChurnAnalysis.jpynb: Telecom Customer Churn Prediction with 6 models and simple keras
- 93_cnn_Tensorflow.jpynb: Flower image classfication with Tensorflow
- 94_cnn_NeuralStyler.ipynb: Neural Style Transfer with Tensorflow
- 95_cnn_invasive.jpynb: Image dector for invasive species of Hydrangea (Unable to run due to limitness of my machine...)
- 96_cnn_doodle.ipynb: Image classification of quick draw
- 97_cnn_digit.ipynb: Simple MNIST digit data. Simple CNN
- 98_cnn_breed.ipynb: Image classification of Dog breeds. Using VGG19
- 99_easiest_CNN.ipynb: Image classification of cats and dogs. Simple CNN