P.01Learn OpenCV fundamentals including image I/O, pixel manipulation, color conversion, resizing, filtering, edge detection, and feature detection with SIFT and SURF.
P.02Understand the divide and conquer algorithmic paradigm through the maximum subarray sum problem, with Python implementation and step-by-step analysis.
P.03EditorPickExploratory data analysis means visualizing, cleaning, and summarizing data before modeling. This guide covers plots, correlation, PCA, and feature engineering.
P.04EditorPickMaster bitwise operations, bitmasking, bit manipulation tricks, and bit-based algorithms for competitive programming and software engineering interviews.
P.05Build a CNN model using ResNet50 transfer learning to classify gender from eye images, covering data preprocessing, model architecture, and evaluation.
P.06A step-by-step guide to writing and publishing research papers in artificial intelligence, machine learning, and deep learning — from ideation to submission.
P.07Learn to predict stock prices using Long Short-Term Memory (LSTM) networks in Python with TensorFlow, from data preprocessing to building and evaluating the model.
P.08A hands-on guide to building a fruit image classifier using transfer learning with ResNet50 in TensorFlow and Keras, achieving high accuracy on the Fruits-360 dataset.