Python. An allrounder language, though a bit slow but very versatile. Python is used in Data Science, ML, DL, Web Devlopment, building applications, automation and many more things.

Many time consuming tasks which are very trivial can be automated using Python.There are many libraries written in Python which help in donig so.

Everyone must have played the dinosaur game in Google Chrome when the Internet is off. A simple game which just takes two buttons to play. …


Natural Language Processing (NLP) deals with the text data in its natural form. The raw text is broken down into tokens and word embeddings(word vectors) which make it easy for the Machine to understand.

In this app we, convert the raw text into tokens and then convert the words into their base form, which are then compared to a dataset of Words matched with their matching emotions.

The count of these emotions is kept and at the end, the overall emotion of the sentence is predicted.

The dataset for this problem statement is obtained from http://sentiment.nrc.ca/lexicons-for-research/

NRC Lexicon Dataset

The dataset has 14000+…


To get started with XGBoost , first we have to install the XGBoost library package. We can do it using ‘pip’ or ‘conda’.

pip install xgboost

In this article we’ll focus on how to create your first ever model (classifier ) with XGBoost.

The data set we choose for this example is the handwritten digit dataset , which is readily available in sklearn’s preloaded datasets. To import the data set we use the code :

from sklearn import datasets
digits = datasets.load_digits()

The digits object has ‘images’ and ‘target’ attributes in it.

The images are 2dimensional arrays of dimension 8x8…

Niketanpanchal

Python | ML | Data Science | Tableau

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