This code is a Python script that loads historical stock data for the Apple Inc. (AAPL) company from Yahoo Finance, preprocesses the data by normalizing it using MinMaxScaler, creates a time series data sequence with a specified sequence length, builds a deep learning model with multiple LSTM layers
Sentiment Analysis is a popular Natural Language Processing (NLP) task that aims to classify the sentiment of a given text as either positive, negative or neutral. In this project, IMDb reviews are used to train and evaluate a Sentiment Analysis model using the oneDAL too
AI and ML can revolutionize road management by analyzing real-time data from sensors and cameras to detect issues and alert authorities, leading to decreased accidents and infrastructure damage. Data generated can train and refine algorithms, leading to more efficient road management.
Plant disease prediction using AI and ML uses artificial intelligence and machine learning techniques to predict plant diseases accurately. This approach utilizes various technologies, including image processing, data analysis, and predictive modeling, promptly and diagnosing plant diseases.
The prevalence of online hate speech and harassment is a significant social issue with potentially severe consequences for individuals and groups. Machine learning has the potential to aid in combating this problem by analysing large amounts of data to identify abusive behaviour patterns.
In this project, we aim to develop a machine-learning model that can accurately predict the likelihood of depression based on social media posts. We will gather a large dataset of social media posts from individuals with and without depression and use natural language processing techniques.
In this project, we aim to develop a machine learning model that can accurately predict the likelihood of depression based on social media posts. We will gather a large dataset of social media posts from individuals with and without depression, and use natural language processing techniques.
My name is Devesh Bhandari and my teammate VS Lavan and We are student at Christ University. This challenge is focused on house price prediction in India, where the goal is to accurately predict the prices of properties using 12 influencing factors.
The pre requisite for this system are mean radius , mean perimeter ,mean area, worst radius, worst perimeter, worst radius ,worst area.
giving this parameter it detects whether it is Malignant or Benign
E-waste is one of the major concerns as of today, and them being a major concern makes it a necessity for its decomposition and recycling more important. We propose an idea to take analysis data of the current situation of the E waste being generated and all its sources and other factors.
Credit card fraud detection systems leverage AI/ML to detect patterns of fraudulent behavior in spending data. They identify anomalies, flag suspicious activity, and improve over time through machine learning. This helps prevent losses for financial institutions and consumers.
The Speech Recognition System is an artificial intelligence-based system that recognizes and transcribes spoken language into written text or other forms of output.
This project aims to build a spam detection system using machine learning algorithms. The goal is to train a machine learning model that can accurately classify messages as spam or not spam. By doing so, we can save time and avoid the hassle of dealing with unwanted messages.
It Predict the white winner in a chess game on the basis of first move of white player and response of black player. In the dataset all the set of moves are given but We choose to predict the white winner the first move.Also it predicts the next move of the player using deep learning techniques
The music generator application with LSTM and RNN neural network is a project that uses machine learning techniques to generate music. The application is designed to take in a dataset of existing music, and then use an LSTM (Long Short-Term Memory) or RNN (Recurrent Neural Network) model to learn th