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Gokul S's Projects

tensorflow-yolov3 icon tensorflow-yolov3

🔥 pure tensorflow Implement of YOLOv3 with support to train your own dataset

tensorflow-yolov4-tflite icon tensorflow-yolov4-tflite

YOLOv4, YOLOv3, YOLO-tiny Implemented in Tensorflow 2.0, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite

tesseract icon tesseract

Tesseract Open Source OCR Engine (main repository)

text_summerization icon text_summerization

Text will be summarized in such a way that only main details will be displayed.

text_summerization-1 icon text_summerization-1

In this project, we used the page rank algorithm to extract important sentences as an extractive summary. We used word2vec representation of words to calculate word similarities.

textsummerisation icon textsummerisation

Using nltk, stopwords, tokenizer and Stemmer i made text summerisation Algorithm. It can generate summary of any type of Text.

the-incredible-pytorch icon the-incredible-pytorch

The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.

tiktok-clone icon tiktok-clone

A clone of TikTok built by Sonny & Qazi 👉 https://tik-tok-clone-eb635.web.app/

time-series-forecasting-of-amazon-stock-prices-using-neural-networks-lstm-and-gan- icon time-series-forecasting-of-amazon-stock-prices-using-neural-networks-lstm-and-gan-

Project analyzes Amazon Stock data using Python. Feature Extraction is performed and ARIMA and Fourier series models are made. LSTM is used with multiple features to predict stock prices and then sentimental analysis is performed using news and reddit sentiments. GANs are used to predict stock data too where Amazon data is taken from an API as Generator and CNNs are used as discriminator.

time-series-prediction-and-text-generation icon time-series-prediction-and-text-generation

Built RNNs that can generate sequences based on input data - with a focus on two applications: used real market data in order to predict future Apple stock prices using an RNN model. The second one will be trained on Sir Arthur Conan Doyle's classic novel Sherlock Holmes and generates wacky sentences based on it that may - or may not - become the next great Sherlock Holmes novel.

topic-modelling-on-wiki-corpus icon topic-modelling-on-wiki-corpus

It uses Latent Dirichlet Allocation algorithm to discover hidden topics from the articles. It is trained on 60,000 articles taken from simple wikipedia english corpus. Finally, It can extract the topic of the given input text article.

transformers icon transformers

🤗 Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch.

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