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bank-marketing-prediction

In the I made the analysis on the bank marketing dataset.

customer-churn-analysis-using-ann

The dataset I used is insurance dataset which is in a csv format. I made the analysis on the dataset using machine learning concepts and have a accuracy of above 80 percent

handwritten-digit-classification-using-keras

Here I used the predefined dataset and using the sequential keras and adjusted the parameters to get the accuracy of 97 percent

iristracking

In this we can able to track a human eye in video as well as in live. More accurate iris tracking. Can be used in the online proctoring system. One type of scoring is provided.

keyword-extraction

In this from a transcripts stored in a text file we can able to extract a keywords we need. For that first we need to first define the keywords. The scoring part is also provided.

keyword-extraction-from-transcripts

In this code, the keywords from the transcripts are extracted in the form of single, bi, tri and tetragrams. i used the package called flashtext. We have to dynamically specify the keywords of our wish.

react-hello-world

regex-to-capture-cgpa-gpa-and-all-kinds-of-date-format-in-python

using regex function, all kinds of date format can be captured

sentiment-analysis-using-spark-nlp-pipeline

Here i used the pyspark and spark nlp with the predefined sentimentdl_use_twitter model. We can add or check any words to the dataframe and get the accurate sentiment which is positive, neutral or negative

spam-filtering-using-naive-bayes

Here I used the Machine learning algorithm naive bayes to filter the contents whether it is a spam or a ham

us-news-scraping-using-json-endpoint

web scraping using a json endpoint in a us news scraping