Biodelta data

Using Facebook' lira as a case study

Data science report

medicine

Cat vs Dogs

test

Speech Recognition

Applying Decision Tree algorithm to Seattle weather data

Deep Learning with Neural Nets

Using wordcloud to gain insights from a large pool of data

In this paper K-Nearest Neighbors will be used to calculate the likelihood if a customer will be a defaulter or not. We will use a historical bank data to construct a predictive loan model.

Goals The goal of this research paper is to show basic credit scoring computations in R programming language

Using Linear Discriminant Analysis To Predict Defaulters Of A Bank Loan

As the bulk of the world's information is online, the task of making that data accessible becomes increasingly important. The challenge of making the world's information accessible to everyone, across language barriers, has simply outgrown the capacity for human translation. Natural language processing, or NLP is a branch of artificial intelligence concerned with the interactions between computers and human (natural) languages, and, in particular, concerned with programming computers to fruitfully process large natural language data. is an important technology in bridging the gap between human communication and digital data. Many NLP applications, including text-to-speech synthesis (TTS) and automatic speech recognition (ASR), require text to be converted from written expressions into appropriate "spoken" forms. This is a process known as text normalization, and helps convert 12:47 to "twelve forty-seven" and $3.16 into "three dollars, sixteen cents." The goal of this project is to automate the process of developing text normalization grammars via machine learning.