ShubhamModi77

Breast-cancer-prediction

• Various classification models were used to identify the type of breast cancer with a dataset of around 600 images. • In our dataset we have the outcome variable or Dependent variable i.e., Y having only two sets of values, either M (Malign) or B(Benign) • So, we used Classification algorithm of supervised learning. Also, the data was visualized in the form of graphs, using python libraries.

Complete-Langchain-Tutorials

Credit_Card_Fraud_Detection

Here I am using the Kaggle data set to predict the credit card frauds. The dataset is highly imbalanced, hence handling the imbalanced dataset is very important. I have implemented 3 different models with different approaches. The descriptions and results can be seen in the python notebooks. The dataset can be found on kaggle

Data_Analysis

Downloading and exploring the data using python pandas

Face-Recognition

face recognition with opencv and also create an Attendance project that will use webcam to detect faces and record the attendance live in an excel sheet.

Football-Predictions

Predictions of football matches for EPL

Google-Gemini-Crash-Course

Handwritten-digit-classification

Handwritten digit classification using tensorflow keras. I have taken mnist data from tensorflow keras

huggingface_hub

The official Python client for the Huggingface Hub.

Human-activity-Recognition-using-Machine-Learning

In this project I have used machine learning algorithm to predict human activities.

ShubhamModi77/Breast-cancer-prediction

• Various classification models were used to identify the type of breast cancer with a dataset of around 600 images. • In our dataset we have the outcome variable or Dependent variable i.e., Y having only two sets of values, either M (Malign) or B(Benign) • So, we used Classification algorithm of supervised learning. Also, the data was visualized in the form of graphs, using python libraries.

ShubhamModi77/Complete-Langchain-Tutorials

ShubhamModi77/Credit_Card_Fraud_Detection

Here I am using the Kaggle data set to predict the credit card frauds. The dataset is highly imbalanced, hence handling the imbalanced dataset is very important. I have implemented 3 different models with different approaches. The descriptions and results can be seen in the python notebooks. The dataset can be found on kaggle

ShubhamModi77/Data_Analysis

Downloading and exploring the data using python pandas

ShubhamModi77/Face-Recognition

face recognition with opencv and also create an Attendance project that will use webcam to detect faces and record the attendance live in an excel sheet.

ShubhamModi77/Football-Predictions

Predictions of football matches for EPL

ShubhamModi77/Google-Gemini-Crash-Course

ShubhamModi77/Handwritten-digit-classification

Handwritten digit classification using tensorflow keras. I have taken mnist data from tensorflow keras

ShubhamModi77/huggingface_hub

The official Python client for the Huggingface Hub.

ShubhamModi77/Human-activity-Recognition-using-Machine-Learning

In this project I have used machine learning algorithm to predict human activities.

ShubhamModi77/Image-classification-using-cnn

Image classification with using tensorflow library. I have used cifar dataset for classification

ShubhamModi77/Kaggle-football-dataset-analysis-using-python

Statistical data analysis of kaggle football dataset using python.

ShubhamModi77/Llama2-Medical-Chatbot

ShubhamModi77/Natural-Language-Processing-With-Disaster-Tweet

Predict which Tweets are about real disasters and which ones are not. I build a machine learning model that predicts which Tweets are about real disasters and which one’s aren’t.

ShubhamModi77/nuuz-ai

ShubhamModi77/Object-Detection

how to detect objects using opencv and python. The Object Detection opencv method will be able to run this in real time with a good amount of accuracy

ShubhamModi77/Predicting_Heart_dieases-using-Machine-Learning

Given clinical parameters about a patient, can we predict whether or not they have heart disease? • In this project we will find accuracy at predicting whether or not a patient has heart disease during the proof of concept. • So, we used Classification algorithm of supervised learning. Also, the data was visualized in the form of graphs, using python libraries

ShubhamModi77/transformer

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

ShubhamModi77/transformers-james