Image classification of 102 category of flowers
Project was about building and image classifier based on 8k+ images which were consisting of 102 different flower categories. I build a classifier which classifies images with 92% accuracy and then tested model on another 2k+ images which were unlabeled. Task was completed in dividing labelled flowers in various folders and then training on them using pytorch.
Tentang Saya
Website - [login to view URL] Youtube - [login to view URL]@CoderzColumn Primary Skill-Set: - Languages: Python - Tools: Jupyter Notebook, PyCharm, VS Code, Git, Github. - Database: Oracle, MySQL, PostgreSQL. - Frameworks: Django, Flask, Bootstrap - Other: Amazon AWS, Google Cloud Engine Python Libraries with Extensive Hands-On: - Data Manipulation: Numpy, Pandas - Data Visualisation: Matplotlib, Bokeh, Seaborn,geopandas,networkx,holoviews, folium - Machine Learning: Scikit-learn, HuggingFace, Statsmodels, Keras,PyTorch, Nltk, Xgboost, - Scraping: beautifulsoup4,requests
