PickAClass · AI Applications (Interdisciplinary) · AI for Agriculture (AgriTech)

Automated Pest & Disease Detection

Build and deploy computer vision models to automatically detect and identify pests, weeds, and diseases from images, enabling early intervention and targeted treatments.

Automated Pest & Disease Detection

Trace Analysis: Debugging with Homotopy and Tensor Patterns

Object-Oriented Python: Building a Student Performance Calculator

Python Multiprocessing: Barrier, Semaphore, and Condition Variables

Working with Hashtables in Python and PowerShell

Image Classification with Azure Custom Vision

Analyzing Python Memory Usage with memory_profiler

OCR APIs with Tesseract, Pytesseract, and FastAPI

CPU Scaling in Python: Threads, Processes, and Futures

Elixir Performance Optimization: Benchmarking with Benchee

Anomaly Detection with PyCaret in Python

Robust Machine Learning Testing with pytest

Face Verification and Recognition with Azure Face SDK

Face Analysis with Python: MediaPipe, Dlib, and DeepFace

Programmatic PDF Compression with Python and PDFTron

Optimizing Support Vector Machines with Grid Search in Python

Building Machine Learning Apps with PyCaret and Streamlit

Speeding Up Python Code with NumPy Vectorization

Python Environment Setup for Facial Recognition

Virtual Makeup with Python: Face Landmark and Lip Color Modification

Python Multiprocessing: Sharing Objects with BaseManager

Analyzing and Fitting NMR FID Signals with Python and SciPy

Hands-On Support Vector Machines: Solving Classification Challenges

Python Image Graphics with Pycairo and Pillow

Introduction to PyCaret: Build and Compare Classification Models