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Learn to build reproducible machine learning pipelines using Python and DVC. Track experiments, manage data versions, and compare model metrics for improved ML workflow efficiency.
Learn to deploy a pre-trained BERT model for sentiment analysis as a REST API using FastAPI, PyTorch, and Hugging Face. Covers project setup, API creation, model integration, and real-time predictions.
Learn to build a sentiment classification model using BERT, Hugging Face, and PyTorch. Covers BERT basics, fine-tuning for sentiment analysis, model training, evaluation, and prediction from raw text.
Learn text preprocessing for sentiment analysis using BERT, Hugging Face, and PyTorch. Covers tokenization, padding, attention masks, dataset creation, and data splitting for NLP tasks.
Explore fundamental data visualization techniques using Matplotlib and Seaborn in Python. Learn to create histograms, box plots, violin plots, bar charts, line charts, scatter plots, and more for effective exploratory data analysis.
Learn to classify traffic signs using transfer learning with PyTorch. Explore data, build datasets, train a pre-trained ResNet model, evaluate performance, and make predictions on new images.
Learn to forecast Coronavirus cases using LSTM and PyTorch. Covers data preprocessing, model building, training, evaluation, and future predictions with real-world time series data.
Comprehensive guide to image processing with OpenCV in Python, covering essential techniques from basic operations to advanced manipulations for computer vision applications.
Explore XGen-7B's capabilities in long sequence modeling, including performance on NLP tasks, code generation, and document comprehension. Hands-on demo using Google Colab.
Build a customer support chatbot using custom knowledge, LangChain, and a private LLM. Learn to create, embed data, and implement conversational and QA chains for real-time responses on a single GPU.
Explore different memory types for ChatGPT chatbots using LangChain, including buffer, summary, window, and vectorstore memory. Learn implementation techniques for coherent conversations.
Learn to analyze cryptocurrency sentiment on Twitter using LangChain and ChatGPT. Create custom prompts, integrate with LLMChain, and build a Streamlit app for real-time sentiment analysis.
Explore LangChain's capabilities with chat models, embeddings, and prompt templates. Learn to enhance responses and stream output for efficient language model integration.
Learn to build a chatbot using Llama 2 and LangChain to answer questions from multiple PDFs. Explore private LLM integration, vector stores, and efficient document retrieval techniques.
Learn to build a Streamlit app for habit scheduling using ChatGPT and LangChain. Integrate Google Sheets, implement efficient prompts, and create an interactive schedule interface for effective time management.
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