Building Smarter AI Assistants: The Role of LLMs

Large Language Models (LLMs) like ChatGPT process and generate human-like text.

They can assist with tasks like coding, summarization, and customer support.

Example: Summarizing Text with an LLM

from transformers import pipeline

summarizer = pipeline("summarization")
print(summarizer("Machine learning is a field of AI that enables computers to learn from data...", max_length=50))

This script summarizes a long text input using an AI model.

AI in Edge Computing: Bringing Intelligence Closer to Devices

AI at the edge allows real-time decision-making on devices like smartphones and cameras. This reduces latency and reliance on cloud computing. Example: Running AI Inference on a Raspberry Pi This script loads a TensorFlow Lite model for edge computing. Read More
How AI is Reshaping Healthcare: Predicting Disease with Data

AI is improving healthcare by diagnosing diseases and recommending treatments. Deep learning models can analyze medical images to detect anomalies. Example: Using CNNs for Medical Image Classification This builds a simple Convolutional Neural Network (CNN) for image classification. Read More
Explainable AI: Making AI Decisions Transparent

Explainable AI (XAI) makes AI decisions more interpretable. Tools like SHAP and LIME provide insights into model predictions. Example: Using SHAP for Model Explainability This code generates a SHAP summary plot to interpret feature importance. Read More
MLOps: Bridging the Gap Between ML Models and Deployment

MLOps streamlines the deployment and monitoring of ML models in production. Tools like Docker, Kubernetes, and TensorFlow Serving are commonly used. Example: Serving a Model with FastAPI This creates a simple API to serve ML model predictions. Read More

Building Smarter AI Assistants: The Role of LLMs

AI in Edge Computing: Bringing Intelligence Closer to Devices

How AI is Reshaping Healthcare: Predicting Disease with Data

Explainable AI: Making AI Decisions Transparent

MLOps: Bridging the Gap Between ML Models and Deployment