โBuilt Naive Bayes text classifier with scikit-learn for categorizing posts. I enjoy visuals, so I added a heat map๐ฅ โRevised GitHub structure for better organization โAnki: Comparing dimensionality reduction methods
- tackled CNNs for image classification w/tf & keras on CIFAR-10 dataset - explored generative vs discriminative models - worked on research summary 'Deep Reinforcement Learning Framework for Column Generation'
- RNNs, text generation w/ TensorFlow & Keras - Anki ML Q: Cross-validation methods - Data preprocessing & feature engineering on Titanic dataset, visualization, unit testing
Day 3 of #100DaysOfML -Learning how to plot visualisations and getting insights of the data. -Finding correlation among several attributes. -Cleaning the data. -Continued with house price prediction model. #MchineLearning#AI#buildinpublic#OpenSource
Day 3 of #100DaysOfML -Learned about train test split manually as well as scikit-learn. -Disadvantages of splitting data manually and all the stratified bias involved with it. -Implemented the code and updated GitHub. #MachineLearning#DataScience #AI#opensource#buildinpublic
Day 1 of #100DaysOfML -Read about fundamentals of Machine Learning and various types. -Implemented simple linear regression using python and sci-kit learn. -Updated GitHub repository. #MachineLearning#buildinpublic #AI#DataScience