fakhre-alam
A data scientist and a R and Python programmer, with an insatiable intellectual curiosity, and the ability to mine hidden gems located within large sets.
Iris Software IncNoida
Pinned Repositories
Data-Wrangling
data_wrangling
Deep-Learning
Python Basics with Numpy (optional assignment) Welcome to your first assignment. This exercise gives you a brief introduction to Python. Even if you've used Python before, this will help familiarize you with functions we'll need. Instructions: You will be using Python 3. Avoid using for-loops and while-loops, unless you are explicitly told to do so. Do not modify the (# GRADED FUNCTION [function name]) comment in some cells. Your work would not be graded if you change this. Each cell containing that comment should only contain one function. After coding your function, run the cell right below it to check if your result is correct. After this assignment you will: Be able to use iPython Notebooks Be able to use numpy functions and numpy matrix/vector operations Understand the concept of "broadcasting" Be able to vectorize code Let's get started!
HPC
Image-Processing-in-Python
Proceesing Images in Python
Loan-Data-Analysis-Report
Data Analysis Report
Metadata-Management
Seminar held By Cdac and Manipal
Qlikview-Components
A library for common Qlikview Scripting tasks
Song-Recommender
Song Recommender Analysis
Stock-Market-Prediction
Using News Article to Predict Stock Market Movements
voting-classifier
I am trying to predict loan outcomes (0, 1) using an unweighted soft voting ensemble classifier (sklearn's VotingClassifier class with voting='soft'). For a given sample, this outputs the class label with highest averaged probability predicted by the component classifiers.
fakhre-alam's Repositories
fakhre-alam/Building-a-Neural-Net-To-Predict-Loan
Neural Network
fakhre-alam/Predicting-House-Price
Projects
fakhre-alam/Loan_data_analysis
Projects