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art044_nn_lstm

Public repository containing materials used in LSTM article

art045_nn_gru

Public repository containing materials used in the GRU article

blog-good

Pawar

chatbot

This is a chatbot application built in Python using Streamlit and the Langchain library. The application allows users to interact with documents (PDFs, DOCX files, Excel files) and websites. Users can ask questions related to the content of the documents or websites, and the chatbot provides answers based on the available information.

chatbot_qa_documents

chatgpt-retrieval-plugin

The ChatGPT Retrieval Plugin lets you easily find personal or work documents by asking questions in natural language.

deeplearning-padhai-best-

All the code files related to the deep learning course from PadhAI

dlproject

fairseq

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

gru-d

GRU-D, a GRU-based model with trainable decays for multivariate time series classification with missing values/irregular samplings

gru-d-1

inspired by 'Recurrent Neural Networks for Multivariate Time Series with Missing Values' pytorch ver

intro-to-llms

lstnet

Multivariate time series forecasting is an important machine learning problem across many domains, including predictions of solar plant energy output, electricity consumption, and traffic jam situation. Temporal data arise in these real-world applications often involves a mixture of long-term and short-term patterns, for which traditional approaches such as Autoregressive models and Gaussian Process may fail.we proposed a novel deep learning framework, namely Long- and Short-term Time-series network (LSTNet), to address this open challenge. LSTNet uses the Convolution Neural Network (CNN) and the Recurrent Neural Network (RNN) to extract short-term local dependency patterns among variables and to discover long-term patterns for time series trends. Furthermore, we leverage traditional autoregressive model to tackle the scale insensitive problem of the neural network model. In our evaluation on real-world data with complex mixtures of repetitive patterns, LSTNet achieved significant performance improvements over that of several state-of-the-art baseline methods

mart-sales-analysis

Predicting the output sales for BMart

multivariate-time-series-data

multivariate_time_series_forecasting

A place to implement state of the art deep learning methods for temporal modelling using python and MXNet.

ocr-on-scanned-pdf-python

Text is extracted from scanned PDF document using OCR in python

opencv-course

Learn OpenCV in 4 Hours - Code used in my Python and OpenCV course on freeCodeCamp.

padhai-course

Repository containing the colab-notebooks of the course i did on deep learning from One-Fourth-Labs

param-share-transformer

PyTorch implementation of Lessons on Parameter Sharing across Layers in Transformers

pdf_to_text

practical-machine-learning-with-python

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

project-saral

python_for_microscopists

https://www.youtube.com/channel/UC34rW-HtPJulxr5wp2Xa04w?sub_confirmation=1

pythondatasciencehandbook

Python Data Science Handbook: full text in Jupyter Notebooks

querry_multiple_docs_using_langchains_llms

randomforestsgls

recommendation_engine

Recommendation systems using python

rest-apis-flask-python

A small repository of projects built in my course, REST APIs with Flask and Python.

sales-and-marketing-analytics

This repository consists of predicting dynamic pricing, churn predictions using sales and marketing data for understanding users' behaviour.