NehaPant14

Analysis-of-e-commerce-sales-data-using-Power-BI

Analysis of e-commerce sales data using Power-BI dashboard

CEEMDAN-LSTM

code

Compilation of R and Python programming codes on the Data Professor YouTube channel.

darts

A python library for user-friendly forecasting and anomaly detection on time series.

Decision-Tree-Classifier-using-Logistic-Regression

Decision Tree classifier using Logistic Regression

Deep-Learning-For-Hackers

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

Density-based-clustering

Density based clustering

Income_cluster_analysis

Link-analysis-of-real-world-directed-network-dataset

Link analysis of real-world directed network dataset

Loan-Prediction

Loan Prediction using Classification Techniques

NehaPant14/Loan-Prediction

Loan Prediction using Classification Techniques

NehaPant14/Density-based-clustering

Density based clustering

NehaPant14/Income_cluster_analysis

NehaPant14/Link-analysis-of-real-world-directed-network-dataset

Link analysis of real-world directed network dataset

NehaPant14/CEEMDAN-LSTM

NehaPant14/Decision-Tree-Classifier-using-Logistic-Regression

Decision Tree classifier using Logistic Regression

NehaPant14/Analysis-of-e-commerce-sales-data-using-Power-BI

Analysis of e-commerce sales data using Power-BI dashboard

NehaPant14/code

Compilation of R and Python programming codes on the Data Professor YouTube channel.

NehaPant14/darts

A python library for user-friendly forecasting and anomaly detection on time series.

NehaPant14/Deep-Learning-For-Hackers

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

NehaPant14/Diffusion-TS

[ICLR 2024] Official Implementation of "Diffusion-TS: Interpretable Diffusion for General Time Series Generation"

NehaPant14/MovieLens

NehaPant14/Surface-Water-Quality-Data-Anomaly-Detection

Surface water quality data analysis and prediction of Potomac River, West Virginia, USA. Using time series forecasting, and anomaly detection : ARIMA, SARIMA, Isolation Forest, OCSVM and Gaussian Distribution

NehaPant14/telemanom

A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.

NehaPant14/TensorFlow-Tutorials

TensorFlow Tutorials with YouTube Videos

NehaPant14/tf-levenberg-marquardt

Tensorflow implementation of Levenberg-Marquardt training algorithm

NehaPant14/Water-Anomaly-Detection-WAD-Autoencoder

The identification of water that is fit for consumption and usage has proven to be a challenge. The parameters of water that are analyzed are typically Temperature, pH, turbidity, SAC etc.To develop an event detector to accurately predict changes in a time series of drinking water composition data, we selected the AE and RBM .