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-text-generation-using-lstm-neural-networks

Generate text using LSTM neural networks. Read data from Word documents, tokenize, and train the model. More documents improve accuracy. LSTM model predicts next word based on context. Generated text is coherent and contextually relevan

algorithms

Algorithms & Data structures in C++.

analyzing_crime_data_in_los_angeles

The Los Angeles Crime Data Analysis and Time Series Forecasting code provides insights into crime patterns and victim characteristics in Los Angeles. The code covers various aspects of data analysis, visualization, and forecasting using crime data.

blockchain-implementation-

Blockchain implementation with python (Flask) code and connect the code with postman to send GET request , to Create a Block (Mine A block), check if the blockchain is valid

e-commerce-data

This dataset consists of orders made in different countries from December 2010 to December 2011. The company is a UK-based online retailer that mainly sells unique all-occasion gifts. Many of its customers are wholesalers. this work has done by Fakher Odeh

implementation-of-sir-model

leetcode-2

🍡 LeetCode Online Judge刷题题解(Java/C++/python/Ruby/Javascript)

machinelearning

Basic Machine Learning and Deep Learning

ml_solutions_guide

ML_Solutions_Guide , offers concise yet comprehensive solutions and guides for common machine learning problems. With clear explanations and code examples, this repository equips you to address real-world challenges effectively. Perfect for beginners and experienced practitioners alike.

modeling-covid-with-sir-model-

netflixmoviedata

Python script that analyzes a Netflix dataset containing information about movies and TV shows available on Netflix. The script performs various analyses and visualizations to gain insights into the dataset

reinforcement-learning-agent-for-learning-addition

This project implements a reinforcement learning agent to solve simple addition problems. The agent learns to select the correct number to add to the first number in an addition problem using Q-learning. Visualization includes the agent's learning progress and its problem-solving process.

reinforcement-learning-for-function-derivative-estimation

text-summarization-using-bart-model

In this project, we explore text summarization using the BART (Bidirectional and Auto-Regressive Transformers) model, a state-of-the-art sequence-to-sequence model developed by Facebook AI. We utilise the CNN-DailyMail dataset, which contains news articles paired with human-generated summaries.

textextractionmachinelearning