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1. Recognizing-a-sign-with-Deep-Learning-Tensorflow Recognizing-a-sign-with-Deep-Learning-Tensorflow Public

   My goal is to build an algorithm capable of recognizing a sign with high accuracy. To do so, I am going to build a tensorflow model with deep learning methods.

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2. GBM-Classification-on-Spam-Email GBM-Classification-on-Spam-Email Public

   This project about the GBM classification model on spam email data set and model optimisation.

   R 1

3. Speech-recognition-model-development---NLP Speech-recognition-model-development---NLP Public

   Using Speech Commands Dataset to build an algorithm that understands simple spoken commands. By improving the recognition accuracy of open-sourced voice interface tools, we can improve product effe…

   Jupyter Notebook 1 1

4. K-Means-PCA-the-Breast-Cancer-Wisconsin-dataset K-Means-PCA-the-Breast-Cancer-Wisconsin-dataset Public

   K-means is a least-squares optimization problem, so is PCA. k-means tries to find the least-squares partition of the data. PCA finds the least-squares cluster membership vector.

   Jupyter Notebook 4 1

5. M2-Kernel-Methods M2-Kernel-Methods Public

   Kernel Versions of various machine learning algorithms. The following algorithms are checked by applying the kernel trick: PCA • KMeans • LASVM • One class SVM • Passive aggressive online algorithm

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6. Image-Classification Image-Classification Public

   An application to recognise the cat images with the Accuracy of 80 %. From this project, I've learn how to: Build the general architecture of a learning algorithm, including: Initializing parameter…

   Jupyter Notebook 1