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matbilml's Projects

deep-learning-neural-network-editor icon deep-learning-neural-network-editor

Applied Recurrent Neural Network to build a text editor that can capture words that user types in, analyze the entire sequence of them and finally give prediction for the next word.

deep-ttf icon deep-ttf

Survival analsyis and time-to-failure predictive modeling using Weibull distributions and Recurrent Neural Networks in Keras

deeplearning.ai-summary icon deeplearning.ai-summary

This repository contains my personal notes and summaries on DeepLearning.ai specialization courses. I've enjoyed every little bit of the course hope you enjoy my notes too.

densepose icon densepose

A real-time approach for mapping all human pixels of 2D RGB images to a 3D surface-based model of the body

detectron icon detectron

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

drit icon drit

Learning diverse image-to-image translation from unpaired data

fasttext icon fasttext

Library for fast text representation and classification.

goruntu-isleme-klavuzu icon goruntu-isleme-klavuzu

Bu eğitim, bilgisayarlı görünün temellerini anlayabilmenizi ve OpenCV ile bilgisayarlı görü uygulamaları geliştirebilmenizi amaçlamaktadır. Python, Java, JavaScript, C# ve C++ örnekleri ile desteklenmektedir.

handson-ml icon handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

homemade-machine-learning icon homemade-machine-learning

🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

human-activity-recognition-using-recurrent-neural-nets-rnn-lstm-and-tensorflow-on-smartphones icon human-activity-recognition-using-recurrent-neural-nets-rnn-lstm-and-tensorflow-on-smartphones

This was my Master's project where i was involved using a dataset from Wireless Sensor Data Mining Lab (WISDM) to build a machine learning model to predict basic human activities using a smartphone accelerometer, Using Tensorflow framework, recurrent neural nets and multiple stacks of Long-short-term memory units(LSTM) for building a deep network. After the model was trained, it was saved and exported to an android application and the predictions were made using the model and the interface to speak out the results using text-to-speech API.

imbalanced-learn icon imbalanced-learn

Python module to perform under sampling and over sampling with various techniques.

imgaug icon imgaug

Image augmentation for machine learning experiments.

kefir icon kefir

Kefir is a natural language processing kit for Turkic languages

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