Alok Nayak aloknayak29

Data Scientist (Full stack data science role)

9 followers · 28 following

India
in/alok-nayak-24419b5a

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aloknayak29 / pandas_dataframe_table_with_image_and_text.py

Created June 6, 2025 14:35

This is a python script created by LLM to create an html template with image and a pandas dataframe based table. Without any dependencies like jinja

	import pandas as pd

	df = pd.DataFrame({
	'Name': ['Alice', 'Bob', 'Charlie'],
	'Age': [25, 30, 35],
	'City': ['Delhi', 'Mumbai', 'Bangalore']
	})

	html_template = """
	<!DOCTYPE html>

aloknayak29 / ft_wiki_preproc.py

Created July 29, 2017 08:00 — forked from bittlingmayer/ft_wiki_preproc.py

fastText pre-trained vectors preprocessing

	# See https://github.com/facebookresearch/fastText/blob/master/get-wikimedia.sh
	#
	# From https://github.com/facebookresearch/fastText/issues/161:
	#
	# We now have a script called 'get-wikimedia.sh', that you can use to download and
	# process a recent wikipedia dump of any language. This script applies the preprocessing
	# we used to create the published word vectors.
	#
	# The parameters we used to build the word vectors are the default skip-gram settings,
	# except with a dimensionality of 300 as indicated on the top of the list of word

aloknayak29 / basic_prototyping.ipynb

Last active March 23, 2017 09:36

Usage of sklearn models like logistic regression, linear SVM, Randomforests,Multi layered perceptron (feed forward artificial neural network), truncated SVD. Bag of words text preprocessing using countvectorizer etc. Usage of scikit-learn pipelines with pretrained transformers. Voting based ensemble of different classifiers

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aloknayak29 / logistic_data.ipynb

Created November 14, 2016 05:14

gps_data

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aloknayak29 / main_pipelines.py

Created April 13, 2015 10:19

gridsearchcv cross validation, pipelining mmodels, Extending models

	import numpy as np
	from sklearn import linear_model
	from sklearn.feature_extraction.text import TfidfVectorizer
	from sklearn.feature_extraction.text import CountVectorizer
	from sklearn.cross_validation import train_test_split
	import sklearn
	import json
	from sklearn.externals import joblib
	from sklearn.pipeline import make_pipeline
	from sklearn.grid_search import GridSearchCV

aloknayak29 / sentiment_analysis.ipynb

Created December 12, 2014 06:53

sentiment analysis of movie reviews using NLTK naive bayes

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aloknayak29 / gudtimesbadtimes.ipynb

Created November 23, 2014 15:06

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aloknayak29 / sudoku_solver.py

Created July 15, 2012 20:30

sudoku solver solve incomplete valid sudoku matrix using recursive backtrack ,little clever(find valid numbers group once instead validating each [1-9] number) as it could solve hard sudoku puzzle without getting timeout on udacity's sever .(created for u

	# CHALLENGE PROBLEM:
	#
	# Use your check_sudoku function as the basis for solve_sudoku(): a
	# function that takes a partially-completed Sudoku grid and replaces
	# each 0 cell with a number in the range 1..9 in such a way that the
	# final grid is valid.
	#
	# There are many ways to cleverly solve a partially-completed Sudoku
	# puzzle, but a brute-force recursive solution with backtracking is a
	# perfectly good option. The solver should return None for broken