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Top 50 Data Science Projects

Top 50 Data Science Projects

What is Data Science

Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data. Top 50 Data Science Projects are insights based on numbers, statistics, and trends from data that are used to make decisions towards achieving a specific business goal.

 

Top 50 Data Science Projects

  1. Bitcoin Price Prediction using Machine Learning | Python
  2. Employee Attrition using Machine Learning
  3. Groundwater level Prediction
  4. Intrusion Detection using Classification
  5. Hotel review rating classification using NLP
  6. Election Results prediction based on Twitter data
  7. Arabic Natural Language Processing
  8. Road accident analysis and classification
  9. Human activity Recognition
  10. Crime Analysis using K means
  11. Detecting Malware Websites
  12. Liver Disease prediction
  13. Loan approval prediction
  14. Hate speech Detection Using Machine learning
  15. Stock market prediction using Classification
  16. Student Performance analysis
  17. Student feedback classification using Random Forest
  18. Credit card fraud detection using Deep learning
  19. Fake News detection using machine learning
  20. Fake profile identification Machine learning
  21. Rainfall prediction using machine learning
  22. Cyber Threat Analysis on Android Apps
  23. Student Performance Prediction – Machine Learning
  24. Hashtag Clustering using NLP | Machine Learning
  25. KDD & Data Mining Approach for Finding Network Attacks
  26. Churn Modelling Analysis using Deep Learning | Python
  27. Diabetes Prediction using Machine Learning | AI | Python
  28. Student Placement Prediction using AI | Machine Learning
  29. Text Summarization using NLP I Machine Learning
  30. Rating Prediction using Machine Learning
  31. Smart Farming using Machine Learning
  1. Bitcoin Price Prediction using Machine Learning | Python

This approach to check the inefficiency of the cryptocurrency market is often exploited to get abnormal profits. It analyzed stock market prediction; these methods might be effective also in predicting cryptocurrency prices.

  1. Employee Attrition using Machine Learning

A machine learning model is the output generated when coaching a machine learning algorithm with data. After training, it provides a model with input and output. It is often utilized in real-time to find out from data.

The improvements in accuracy are a result of the training process and automation that are a part of machine learning.

 

  1. Groundwater level Prediction

Groundwater level prediction captures trends in water levels in wells and the rainfall model explores the correlation between the rainfall levels and water levels. The periodic are developed only using the water level data of wells while the rainfall model also uses the rainfall data.

 

  1. Intrusion Detection using Classification

The intrusion detection system is a system that monitors and analyzes data to detect intrusion in the system or network. High volume, variety, and high speed of data generated in the network have made the data analysis process to detect attacks by traditional techniques very difficult.

 

  1. Hotel review rating classification using NLP

The hotel review rating classification technique allows machines to read and understand human emotions and extract useful insights for many businesses to grow and develop in the field. Hotel reviews collected from the guests can be classified into three subclasses positive, negative, or neutral and therefore they can analyze the sentiment of the customer.

 

  1. Election Results prediction based on Twitter data

Sentiment analysis methods have been used to improve the predictive results of counting methods. It is significant in relation to the observation period, the data collection and cleansing methods, and the performance evaluation strategy.

 

  1. Arabic Natural Language Processing

This oversight by developing tools and techniques that deliver state-of-the-art performance in a variety of language processing tasks. Machine translation is the most active area of research but also worked on statistical parsing and part-of-speech tagging.

 

  1. Road accident analysis and classification

It can be detected by developing an accurate prediction model which will be capable of automatic separation of various accidental scenarios. The cluster will be useful to prevent accidents and develop safety measures.

It acquires maximum possibilities of accident reduction by using some scientific measures.

  1. Human activity Recognition

It utilizes smart data as a means of learning and discovering human activity patterns for health care applications. This uses frequent pattern mining, cluster analysis, and prediction to measure and analyze energy usage changes sparked by occupants’ behavior.

  1. Crime Analysis using K means

This system will prevent crime from occurring in society. It is analyzed which is stored in the database. The data mining algorithm will extract information and patterns from the database.

It will be done based on places where the crime occurred, and gangs who were involved in the crime took place. This will help to predict crimes that will occur in the future.

 

  1. Detecting Malware Websites

Detecting Malicious Web sites promotes the growth of Internet criminal activities and constrains the development of Web services. It develops systemic solutions to stop the user from visiting such Web sites.

It eliminates the possibility of exposing users to browser-based vulnerabilities.

 

  1. Liver Disease prediction

This dataset was used to evaluate prediction algorithms in an effort to reduce the burden on doctors. It will take the results of how much percentage of patients who get the disease as positive information and negative information.

Then, outputs shown from the proposed classification model indicate the Accuracy in predicting the result.

 

  1. Loan approval prediction

It reduces the risk factors behind selecting a safe person so as to save lots of bank efforts and assets. The analysis will be done to find the most relevant attributes, and the factors that affect prediction result the most.

 

  1. Hate speech Detection Using Machine learning

The exponential growth of social media such as Twitter and community forums has revolutionized communication and content publishing and is also increasingly exploited for the propagation of hate speech and the organization of hate-based activities.

 

  1. Stock market prediction using Classification

Stock market prediction is the act of trying to determine the future value of a stock from social media social media offers a robust outlet for people’s thoughts and feelings Analysis of social media is strongly related to sentiment analysis.

It is used for analyzing social network content and improves the average accuracy.

 

  1. Student Performance analysis

The proposed framework analyzes the students’ demographic data, and study-related and psychological characteristics to extract all possible knowledge from students, teachers, and parents. The highest possible accuracy in academic performance prediction using a set of powerful data mining techniques.

 

  1. Student feedback classification using Random Forest

The models for detecting student states and for associating adaptive system strategies with such states were learned from tutoring dialogue corpora using new data-driven methods.

 

  1. Credit card fraud detection using Deep learning

It mainly focused on credit card fraud detection using Deep Learning. After the classification process of the random algorithm to analyze the data set and the user provides the current dataset.

It will apply the processing of some of the attributes provided can find affected fraud detection in viewing the graphical model visualization.

  1. Fake News detection using machine learning

It describes incorrect and misleading articles published mostly for the purpose of making money through page views. Fake news detection using machine learning has been focusing on classifying online reviews and publicly available social media posts.

  1. Fake profile identification Machine learning

This method can be extended on any platform that needs classification to be deployed on public profiles for various purposes. It uses available information which makes it convenient for organizations to avoid any breach of privacy.

The organizations use private data to further extend the capabilities of the proposed model.

 

  1. Rainfall prediction using machine learning

Prediction of rainfall gives awareness to people and know in advance about rainfall to take certain precautions to protect the crop from rainfall. It was concluded the enhancements, optimizations, and integrations of data mining methods are vital to exploring and solving these problems.

 

  1. Cyber Threat Analysis on Android Apps

It is an effective and efficient malicious applications detection tool needed to tackle and handle new complex malicious apps created by hackers. With the idea of using machine learning approaches to detect the malicious android application.

 

  1. Student Performance Prediction – Machine Learning

Performance analysis of outcomes based on learning is a system that will strive for excellence at different levels and diverse dimensions in the field of students’ interests. It analyzes the student’s demographic data, and psychological characteristics to extract all possible knowledge

 

  1. Hashtag Clustering using NLP | Machine Learning

Hashtag prediction is the task of mapping text to its accompanying hashtags. In this process, a hashtag prediction shows a useful surrogate for learning good representations of text.

This hashtag-based detailed query shows the result as to whether it will be positive or negative and random forest algorithm.

 

  1. KDD & Data Mining Approach for Finding Network Attacks

With emerge of Big Data, the traditional techniques become more complex to deal with Big Data. It intends to use Big Data techniques to produce high-speed and accurate intrusion detection systems.

The results of the experiment showed that the model has high performance and efficiency for Big Data.

 

  1. Churn Modelling Analysis using Deep Learning | Python in Top 50 Data Science Projects

Deep learning is usually associated with having a high number of input layers, one or more hidden layers that connect input layers and perform computational algorithms to determine a probability to predict.

  1. Diabetes Prediction using Machine Learning | AI | Python in Top 50 Data Science Projects

This data set consists of information on users’ age, and type of symptoms related to diabetes. Data is classified and shown in the form of different graphs. The easy data analysis will show results of medical information of changes of getting diabetes on universal plots.

 

  1. Student Placement Prediction using AI | Machine Learning in Top 50 Data Science Projects

The main purpose of this research is to develop machine learning algorithms for predicting the percentage of student placement based on the data related to the university’s academic reputation, opportunities in the city where the university is located, and facilities and cultural opportunities of the university.

  1. Text Summarization using NLP I Machine Learning in Top 50 Data Science Projects

The method of extracting these from the original huge text without losing vital information. It is to identify the important sections, interpret the context and reproduce them in a new way.

This ensures that the core information is conveyed through the shortest text possible.

 

  1. Rating Prediction using Machine Learning in Top 50 Data Science Projects

The review text content analysis uses the principles of the natural language process. This method insights can be drawn from the relationship between customers and items.

This is based on recommended systems, specific to the collaborative filter, and focuses on the reviewer’s point of view.

 

  1. Smart Farming using Machine Learning in Top 50 Data Science Projects

Agriculture is the backbone of the Indian economy. Machine learning techniques are in use to predict and yield of the crop. It analyzes the data and processes the data to get better predictions.

This improves the performance of machine learning models and builds an easy-to-use web application.

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