Korean OCR Model Design(한글 OCR 모델 설계)

Assignment-06-Logistic-Regression. Output variable -> y y -> Whether the client has subscribed a term deposit or not Binomial ("yes" or "no") Attribute information For bank dataset Input variables: # bank client data: 1 - age (numeric) 2 - job : type of job (categorical: "admin.","unknown","unemployed","management","housemaid","entrepreneur","st…

A US-based housing company named Surprise Housing has decided to enter the Australian market. The company uses data analytics to purchase houses at a price below their actual values and flip them on at a higher price.

When Will We Arrive? A Novel Multi-Task Spatio-Temporal Attention Network Based on Individual Preference for Estimating Travel Time

Keras implementation of multi-label classification of movie genres from IMDB posters

Classification - Term Deposit Opening Decision

Analysis of Terry Stops in Seattle

Provides insights on relocating to 2020s hotspot: Texas. Link to project report below.

Understand the learning process of RNNs and discover the LSTM network architecture. Solve problems and perform Natural Language Processing using sequences of data

Using different technique to deal with Text Classification for Sentimental Analsysi from the a base TF-IDF encoding to pre-trained sentence embeddings.

Used libraries and functions as follows:

Recognize underfitting and overfitting, implement bagging and boosting, and build a stacked ensemble model using a number of classifiers.

Experiments in the field of Sentiment Analysis using ML Algorithms namely Logistic Regression, Naive Bayes along with tfidf, one hot encoding, bag of words vectorization. Different MLP and RNN models viz. LSTM, GRU, Bidirectional LSTM. Lastly, state of the art BERT model

Case-based Reasoning (CBR) System

This Program is for Prediction of Crop Recommendation based on Rainfall,Humidity,Amount of Potassium and Amount of Nitrogen

The aim of this project is to classify the faces. Olivetti Faces dataset has been used. In this dataset there are ten different images of each of 40 distinct subjects. For some subjects, the images were taken at different times, varying the lighting, facial expressions (open / closed eyes, smiling / not smiling) and facial details (glasses / no …

Credito - Credit Risk Analysis using XGBoost Classifier with RandomizedSearchCV for loan approval decisions.