Deep Learning Projects , Machine Learning Projects , Python Projects

Liver Disease prediction with 99% accuracy using Convolutional Neural Network and ML model

Introduction:

As a final year student, choosing a compelling and impactful project is crucial for showcasing your skills and knowledge. Liver disease prediction with 99% accuracy is good to choose, an area of growing significance in the healthcare field, offers an excellent opportunity to apply advanced machine learning techniques. In this blog post, we will explore how Convolutional Neural Networks (CNNs) and Decision Trees (DT) can be harnessed to predict liver disease, presenting an exciting and relevant final year project idea.

  1. Understanding Liver Disease:
    Liver disease, is the more life threatening disease. It is important to detect early. The early detection helps in extending life of patients.
  2. Convolutional Neural Networks (CNNs):
    2.1. Introduction to CNNs: CNNs as a powerful deep learning technique widely used in computer vision applications. CNN has convolutional layers, pooling layers, and fully connected layers.
    2.2. CNNs for Liver Disease Prediction: Explore how CNNs can be adapted for liver disease prediction by utilizing medical images such as ultrasound or MRI scans. Discuss the steps involved in data preprocessing, model architecture design, training, and evaluation.
    2.3. Benefits and Limitations of CNNs: The advantages of CNNs in capturing intricate patterns in medical images, enabling high accuracy in disease prediction. Potential limitations are the need for sufficient data and computational resources.
  3. Decision Trees (DT):
    3.1. Introduction to Decision Trees: Decision trees is a versatile machine learning algorithm used for classification tasks.
    3.2. DT for Liver Disease Prediction: The application uses decision trees in predicting liver disease .
    3.3. Benefits and Limitations of DT: Decision trees has ease of interpretability, ease of implementation, and handling missing values. It has the potential limitations, such as overfitting and sensitivity to small changes in the training data.
  4. Comparative Analysis:
    Compare the performance and characteristics of CNNs and decision trees for liver disease prediction. Liver disease prediction with 99% accuracy whereas Decision tree achieved very less than this. Discuss their strengths and weaknesses in terms of accuracy, interpretability, computational requirements, and suitability for different data types. Encourage students to consider the trade-offs when choosing between these two approaches.
  5. Conclusion:
    Liver disease prediction with 99% accuracy using Convolutional Neural Networks in predicting liver disease is more accurate than using machine learning technique Decision Tree.

Python demo video

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Belly Pain

Burping

Discomfort

Hungry

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Landslide prediction using Machine Learning algorithms

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Machine Learning Projects , Python Projects

Stock Price Prediction using Hyper tuned ML models

Stock price prediction has long been a challenging problem in the financial industry, with researchers and practitioners continuously seeking more accurate and robust methods. This study explores the application of hyperparameter-tuned machine learning (ML) models for stock price prediction. Leveraging the power of advanced ML algorithms and hyperparameter optimization techniques, this research aims to improve the accuracy of stock price forecasts and provide insights into the effectiveness of different models.

Algorithms Used

Decision Tree algorithm

KNN algorithm

Random forest algorithm

The research begins by collecting historical stock price data, along with relevant financial indicators and market sentiment features. Hyperparameter optimization techniques such as grid search optimization are then applied to fine-tune the models and enhance their predictive performance.

Python Demo

The stock price prediction project also implemented using

Clustering Analysis

www.finalsemprojects.com/stock-prediction-using-clustering-and-classification-model/

Stock price prediction using deep learning project demo can be seen here

www.finalsemprojects.com/stock-price-prediction-in-machine-learning-and-deep-learning/