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6G Technology

May 28, 2018

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Image Classification with TensorFlow: Predicting Flowers from Photos

🌼 Image Classification with TensorFlow: Predicting Flowers from Photos Have you ever wondered how machines recognize images? Whether it's identifying flowers, animals, or handwritten digits, image classification is one of the most exciting applications of deep learning. In this post, I’ll walk you through a simple image classification project I built using TensorFlow and Keras. We’ll load a trained model, preprocess an image, make predictions, and visualize the result—all in just a few lines of Python. 🧠 What This Project Does Loads a flower image from disk. Preprocesses it to match the model’s input format. Uses a trained neural network to predict the flower type. Displays the image along with the predicted label and confidence score. 🛠️ Tools and Libraries Used TensorFlow/Keras : For loading the model and making predictions. Matplotlib : To visualize the image and prediction. NumPy : For numerical operations. Keras Preprocessing : For image loading and transformation. 📸 Ste...

Validating a Sudoku Board in Python

Validating a Sudoku Board in Python Sudoku is a classic puzzle that challenges players to fill a 9×9 grid so that each row, column, and 3×3 subgrid contains all digits from 1 to 9 without repetition. While solving it is fun, validating a given board programmatically is a great exercise in logic and Python skills. In this post, I’ll walk you through how I built a Python function to validate a Sudoku board. The goal is to check whether the board follows the rules of Sudoku—even if it's not fully solved. 🔍 Problem Statement Given a 9×9 board filled with digits '1' to '9' and empty cells represented by '.' , determine if the board is valid. A valid board must satisfy: Each row contains unique digits. Each column contains unique digits. Each 3×3 subgrid contains unique digits. 🧠 My Solution Strategy I broke the problem into three parts: Validate each row. Validate each column. Validate each 3×3 subgrid. Here’s the complete code: from typing import List ...

Building an Intent-Based Chatbot Using TensorFlow and NLTK

🤖 Building an Intent-Based Chatbot Using TensorFlow and NLTK Chatbots are everywhere—from customer support to virtual assistants—and building one from scratch is a fantastic way to dive into natural language processing and machine learning. In this post, I’ll walk you through how I built a simple intent-based chatbot using Python, TensorFlow, and NLTK. 🧠 What Is an Intent-Based Chatbot? Unlike generative chatbots that try to generate human-like responses, intent-based chatbots classify user input into predefined categories (called intents ) and respond accordingly. For example, if a user says “Hi,” the bot might classify it as a greeting intent and reply with “Hello! How can I help you?” 🛠️ Tools and Libraries Used NLTK : For tokenization and lemmatization. TensorFlow/Keras : To build and train the neural network. JSON : To store intents and training patterns. Pickle : For saving processed data. NumPy : For numerical operations. 📁 Step 1: Preparing the Data We start by loadi...

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