Upload 2 files

courses.csv

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+title,description,keywords
+Machine Learning Basics,"Understand the fundamentals of statistics, including probability distributions and hypothesis testing.","Data Engineering, ETL"
+Computer Vision with Python,Explore computer vision techniques and applications using Python libraries.,"Machine Learning, AI"
+Natural Language Processing Essentials,"This course covers the basics of data science, including data analysis and visualization.","Python, Data Analysis"
+Introduction to Data Science,Get started with natural language processing using Python and popular NLP libraries.,"AI, Beginners"
+Data Engineering Concepts,"Explore advanced topics in deep learning, including neural networks and backpropagation.","Machine Learning, AI"
+Machine Learning Basics,"This course covers the basics of data science, including data analysis and visualization.","Computer Vision, Python"
+Computer Vision with Python,"Explore advanced topics in deep learning, including neural networks and backpropagation.","Computer Vision, Python"
+Introduction to Data Science,"Understand the fundamentals of statistics, including probability distributions and hypothesis testing.","Machine Learning, AI"
+Computer Vision with Python,Learn how to create stunning visualizations with libraries such as Matplotlib and Seaborn.,"Data Engineering, ETL"
+Machine Learning Basics,Learn how to create stunning visualizations with libraries such as Matplotlib and Seaborn.,"Computer Vision, Python"
+Python for Data Analysis,An introduction to artificial intelligence concepts and applications for beginners.,"Machine Learning, AI"
+Advanced Deep Learning,"Learn data engineering concepts such as ETL, data pipelines, and big data.","AI, Beginners"
+Computer Vision with Python,A beginner-friendly course on data analysis using Python libraries like Pandas and Numpy.,"Python, Data Analysis"
+Introduction to Data Science,"Learn data engineering concepts such as ETL, data pipelines, and big data.","Data Engineering, ETL"
+Data Engineering Concepts,A beginner-friendly course on data analysis using Python libraries like Pandas and Numpy.,"Deep Learning, Neural Networks"
+Data Visualization with Python,"Explore advanced topics in deep learning, including neural networks and backpropagation.","Visualization, Matplotlib"
+Machine Learning Basics,Explore computer vision techniques and applications using Python libraries.,"Visualization, Matplotlib"
+Machine Learning Basics,Learn how to create stunning visualizations with libraries such as Matplotlib and Seaborn.,"Computer Vision, Python"
+Statistics Fundamentals,Learn the foundational concepts of machine learning and how to apply them.,"AI, Beginners"
+Data Visualization with Python,Learn how to create stunning visualizations with libraries such as Matplotlib and Seaborn.,"Data Engineering, ETL"
+Introduction to Data Science,Explore computer vision techniques and applications using Python libraries.,"Data Science, Python, Visualization"
+Statistics Fundamentals,Explore computer vision techniques and applications using Python libraries.,"Machine Learning, AI"
+Computer Vision with Python,"This course covers the basics of data science, including data analysis and visualization.","Deep Learning, Neural Networks"
+Python for Data Analysis,Learn how to create stunning visualizations with libraries such as Matplotlib and Seaborn.,"Data Science, Python, Visualization"
+Advanced Deep Learning,Learn the foundational concepts of machine learning and how to apply them.,"AI, Beginners"
+Introduction to Data Science,Explore computer vision techniques and applications using Python libraries.,"Data Engineering, ETL"
+Data Engineering Concepts,Get started with natural language processing using Python and popular NLP libraries.,"NLP, Language Processing"
+Statistics Fundamentals,Learn how to create stunning visualizations with libraries such as Matplotlib and Seaborn.,"Deep Learning, Neural Networks"
+Python for Data Analysis,"Learn data engineering concepts such as ETL, data pipelines, and big data.","Data Engineering, ETL"
+Computer Vision with Python,Explore computer vision techniques and applications using Python libraries.,"Python, Data Analysis"
+Data Engineering Concepts,"Understand the fundamentals of statistics, including probability distributions and hypothesis testing.","Data Science, Python, Visualization"
+AI for Beginners,Get started with natural language processing using Python and popular NLP libraries.,"Statistics, Probability"
+Python for Data Analysis,"Learn data engineering concepts such as ETL, data pipelines, and big data.","NLP, Language Processing"
+Python for Data Analysis,Learn how to create stunning visualizations with libraries such as Matplotlib and Seaborn.,"Data Engineering, ETL"
+Computer Vision with Python,Learn the foundational concepts of machine learning and how to apply them.,"Machine Learning, AI"
+Natural Language Processing Essentials,Learn how to create stunning visualizations with libraries such as Matplotlib and Seaborn.,"Data Engineering, ETL"
+Computer Vision with Python,A beginner-friendly course on data analysis using Python libraries like Pandas and Numpy.,"Statistics, Probability"
+Advanced Deep Learning,"Understand the fundamentals of statistics, including probability distributions and hypothesis testing.","Deep Learning, Neural Networks"
+Python for Data Analysis,An introduction to artificial intelligence concepts and applications for beginners.,"Computer Vision, Python"
+Data Engineering Concepts,An introduction to artificial intelligence concepts and applications for beginners.,"AI, Beginners"
+Machine Learning Basics,A beginner-friendly course on data analysis using Python libraries like Pandas and Numpy.,"Deep Learning, Neural Networks"
+Advanced Deep Learning,Explore computer vision techniques and applications using Python libraries.,"Deep Learning, Neural Networks"
+Statistics Fundamentals,"This course covers the basics of data science, including data analysis and visualization.","Statistics, Probability"
+Statistics Fundamentals,A beginner-friendly course on data analysis using Python libraries like Pandas and Numpy.,"Machine Learning, AI"
+Python for Data Analysis,An introduction to artificial intelligence concepts and applications for beginners.,"Data Science, Python, Visualization"
+Advanced Deep Learning,"Understand the fundamentals of statistics, including probability distributions and hypothesis testing.","Python, Data Analysis"
+AI for Beginners,Learn the foundational concepts of machine learning and how to apply them.,"Data Engineering, ETL"
+Data Visualization with Python,"Explore advanced topics in deep learning, including neural networks and backpropagation.","Visualization, Matplotlib"
+Python for Data Analysis,An introduction to artificial intelligence concepts and applications for beginners.,"NLP, Language Processing"
+Machine Learning Basics,Learn how to create stunning visualizations with libraries such as Matplotlib and Seaborn.,"NLP, Language Processing"

da.py

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+# -*- coding: utf-8 -*-
+"""Da.ipynb
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1Kg9-C_Fif3yO8FuXT84Tci-3ItuLsS7p
+"""
+
+#Library install
+!pip install transformers sentence-transformers gradio
+
+import pandas as pd
+from sentence_transformers import SentenceTransformer
+from sklearn.metrics.pairwise import cosine_similarity
+import gradio as gr
+
+# Load the dataset
+df = pd.read_csv('/content/courses.csv')  # Replace with actual path to courses.csv
+
+# Load a pre-trained sentence transformer model
+model = SentenceTransformer('all-MiniLM-L6-v2')
+
+# Create a combined column for embedding (e.g., title + description + keywords)
+df['combined_text'] = df['title'] + " " + df['description'] + " " + df['keywords']
+course_embeddings = model.encode(df['combined_text'].tolist(), convert_to_tensor=True)
+
+def search_courses(user_query):
+    # Encode the user query
+    query_embedding = model.encode(user_query, convert_to_tensor=True)
+
+    # Compute cosine similarities between the query and each course embedding
+    similarities = cosine_similarity(
+        query_embedding.cpu().detach().numpy().reshape(1, -1),
+        course_embeddings.cpu().detach().numpy()
+    )
+
+    # Get indices of top matching courses (top 5 results)
+    top_matches = similarities.argsort()[0][-5:][::-1]
+
+    # Retrieve top matching courses
+    results = [{"title": df.iloc[i]["title"], "description": df.iloc[i]["description"]} for i in top_matches]
+    return results
+
+# Define Gradio function for user interaction
+def gradio_search(query):
+    results = search_courses(query)
+    return results
+
+# Set up Gradio interface
+iface = gr.Interface(
+    fn=gradio_search,
+    inputs="text",
+    outputs="json",
+    title="Smart Course Search",
+    description="Find the most relevant courses based on your query."
+)
+
+# Launch the app (for local testing or deploying in Hugging Face Spaces)
+iface.launch()