I have the following specification on my computer: Windows10, 64 bit,Python 3.5 and Anaconda3.I tried many times to install XGBoost but somehow it never worked… Read More »Installing XGBoost for Windows – walk-through
This post is exploratory data analysis with pandas – 1. Clear data plots that explicate the relationship between variables can lead to the creation of newer… Read More »Exploratory Data Analysis with pandas – 1
In [20]: import pandas as pd import numpy as np In [ ]: # Take few samples for the visualization sample_fbcheckin_train_tbl = fbcheckin_train_tbl[:10000].copy() In [21]: df = pd.read_csv(‘train.csv’, index_col=’row_id’)… Read More »Facebook Data Analysis
This blog contains notes for me to understand how to evaluate machine learning algorithms . I want to see how models compare and contrast to… Read More »Evaluating Machine Learning Algorithms
This script is my attempt for time series analysis. Pandas has dedicated libraries for handling TS objects, particularly the datatime64[ns] class which stores time information… Read More »Time Series Forecast using Kobe Bryant Dataset
This part is a Tutorial using Kobe Bryant Dataset – Part 4. You can get the data from https://www.kaggle.com/c/kobe-bryant-shot-selection . What excited me was that… Read More »Tutorial using Kobe Bryant Dataset – Part 4
This part is a kaggle tutorial using Kobe Bryant Dataset – Part 3. You can get the data from https://www.kaggle.com/c/kobe-bryant-shot-selection . What excited me was… Read More »Tutorial using Kobe Bryant Dataset – Part 3
This part is a kaggle tutorial using Kobe Bryant Dataset – Part 1. You can get the data from https://www.kaggle.com/c/kobe-bryant-shot-selection . What excited me was… Read More »Kaggle Tutorial using Kobe Bryant Dataset – Part 1
