All Projects → vimal1083 → Handwritten Character Recognition

vimal1083 / Handwritten Character Recognition

Licence: mit
This a Deep learning AI system which recognize handwritten characters, Here I use chars74k data-set for training the model

Projects that are alternatives of or similar to Handwritten Character Recognition

Tensorflow
Tensorflow实战学习笔记、代码、机器学习进阶系列
Stars: ✭ 1,066 (+1911.32%)
Mutual labels:  jupyter-notebook
Aistudio Searching Data Dumps With Use
searching large heterogenous data dumps with Universal Sentence Encoder
Stars: ✭ 53 (+0%)
Mutual labels:  jupyter-notebook
Visualizing And Understanding Convolutional Neural Networks
Stars: ✭ 53 (+0%)
Mutual labels:  jupyter-notebook
Aws Machine Learning University Accelerated Cv
Machine Learning University: Accelerated Computer Vision Class
Stars: ✭ 1,068 (+1915.09%)
Mutual labels:  jupyter-notebook
Neural Process Family
Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.
Stars: ✭ 53 (+0%)
Mutual labels:  jupyter-notebook
Gan
python notebooks accompanying the book Make Your Own GAN
Stars: ✭ 50 (-5.66%)
Mutual labels:  jupyter-notebook
Average Word2vec
🔤 Calculate average word embeddings (word2vec) from documents for transfer learning
Stars: ✭ 52 (-1.89%)
Mutual labels:  jupyter-notebook
Notebooks
Some notebooks
Stars: ✭ 53 (+0%)
Mutual labels:  jupyter-notebook
365datascience
This Repo Contains all the exercise files for Data Science Course of 365 Datascience . The repo is split into the relevant folders & there is one exercise folder which contains all the files of that course. Don't forget to star it :D
Stars: ✭ 53 (+0%)
Mutual labels:  jupyter-notebook
25daysinmachinelearning
I will update this repository to learn Machine learning with python with statistics content and materials
Stars: ✭ 53 (+0%)
Mutual labels:  jupyter-notebook
Tensorflow Tutorials For Time Series
TensorFlow Tutorial for Time Series Prediction
Stars: ✭ 1,067 (+1913.21%)
Mutual labels:  jupyter-notebook
Figure Gen
A Python package to effortlessly assemble images in comparison figures. Supports LaTeX, PPTX, and HTML.
Stars: ✭ 53 (+0%)
Mutual labels:  jupyter-notebook
Brihaspati
Collection of various implementations and Codes in Machine Learning, Deep Learning and Computer Vision ✨💥
Stars: ✭ 53 (+0%)
Mutual labels:  jupyter-notebook
Fasttext multilingual
Multilingual word vectors in 78 languages
Stars: ✭ 1,067 (+1913.21%)
Mutual labels:  jupyter-notebook
Keras2kubernetes
Open source project to deploy Keras Deep Learning models packaged as Docker containers on Kubernetes.
Stars: ✭ 53 (+0%)
Mutual labels:  jupyter-notebook
Python Tutorial Notebooks
Python tutorials as Jupyter Notebooks for NLP, ML, AI
Stars: ✭ 52 (-1.89%)
Mutual labels:  jupyter-notebook
Transformer Tts
Implementation of "FastSpeech: Fast, Robust and Controllable Text to Speech"
Stars: ✭ 53 (+0%)
Mutual labels:  jupyter-notebook
Homeless Arrests Analysis
A Los Angeles Times analysis of arrests of the homeless by the LAPD
Stars: ✭ 53 (+0%)
Mutual labels:  jupyter-notebook
Data Privacy For Data Scientists
A workshop on data privacy methods for data scientists.
Stars: ✭ 53 (+0%)
Mutual labels:  jupyter-notebook
Policy Gradient Methods
Implementation of Algorithms from the Policy Gradient Family. Currently includes: A2C, A3C, DDPG, TD3, SAC
Stars: ✭ 54 (+1.89%)
Mutual labels:  jupyter-notebook

handwritten-character-recognition

This a Deep learning AI system which recognize handwritten characters, Here I use chars74k data-set for training the model

Prerequisites:

  • Python
  • anaconda
  • Pip
  • virtualenv

Download handwritten dataset from here

It has only 55 samples for each class, so I have written script to create duplicate images with different backgroud color.

Clone this repository and create a virtualenv using below command

virtualenv venv
source venv/bin/activate

Navigate to cloned directory

pip install -r requirements.txt

Create duplicate images for dataset

python generate_dataset.py

Open notebook

jupyter notebook
Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].