Study and implementation about deep learning models, architectures, applications and frameworks
-
Updated
May 26, 2024 - Jupyter Notebook
Study and implementation about deep learning models, architectures, applications and frameworks
Rating: (8/10) The project uses natural language processing to create a chatbot capable of understanding user queries. It trains on a dataset of intents, tokenizing patterns, and constructing a neural network model. The model is saved for future use.
Real-time Facial Emotion Detection using deep learning
Deep learning library featuring a higher-level API for TensorFlow.
The TFLearn-Haiku generator, powered by Tensorflow and TfLearn, is a program that utilizes machine learning to generate haikus. While these haikus are not the best, the show simplicity and usefulness of programs such as this one.
This is a chatbot that will give answers to most of your corona related questions/FAQ. The chatbot will give you answers from the data given by WHO(https://www.who.int/). This will help those who need information or help to know more about this virus.
Predicting Titanic passenger survival through machine learning. This project includes data preprocessing, exploratory data analysis, feature engineering, and model training using Python. 🚢
Repo for self driving cars in GTA-V using Neural Networks and Deep Learning.
lock mechanism with face recognition and liveness detection
A top-down, practical guide to learn AI, Deep learning and Machine Learning.
Deep facial expressions recognition using Opencv and Tensorflow. Recognizing facial expressions from images or camera stream
Equipped YoloV5 and OCR for ANPR and extraction. Trained different ML models to classify images of vehicles.
AI Based Virtual Assistant
Bot Discord dari maskot Union Project. Union-chan yang memiliki teknologi Natural Language Processing
An AI chatbot with features like conversation through voice, fetching events from Google calendar, make notes, or searching a query on Google.
Data Analysis Solution for Titanic passenger data.
Data pipeline and training pipeline for 🎵 music genre classification from FMA dataset
Add a description, image, and links to the tflearn topic page so that developers can more easily learn about it.
To associate your repository with the tflearn topic, visit your repo's landing page and select "manage topics."