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Boyan Angelov boyanangelov

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boyanangelov / tools.md
Created March 15, 2019 11:50
Optimal Tools for ML/AI
  • dplyr
  • pandas
  • ggplot2
  • plotly
  • seaborn
  • mlr
  • scikit-learn
  • yellowbrick
  • xgboost
  • keras
@boyanangelov
boyanangelov / tim_show_scraper.py
Last active December 27, 2018 12:48
Scraping the Tim Ferris Show
from urllib.request import urlopen
from bs4 import BeautifulSoup
from collections import Counter
import pickle
import nltk
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize
from __future__ import division
from nltk import FreqDist
from tqdm import tqdm
@boyanangelov
boyanangelov / optimal_tools_for_ml.md
Last active December 23, 2022 07:49
Optimal Tools for ML/AI

Optimal Tools for ML and AI

Languages

R packages

@boyanangelov
boyanangelov / .gitignore
Created June 7, 2016 21:25
Data Science .gitignore
# R stuff
.Rproj.user
.Rhistory
.RData
.Ruserdata
# datatypes
*csv
*tsv
*xls
@boyanangelov
boyanangelov / nnet_plot_update.r
Created March 20, 2016 14:21 — forked from fawda123/nnet_plot_update.r
nnet_plot_update
plot.nnet<-function(mod.in,nid=T,all.out=T,all.in=T,bias=T,wts.only=F,rel.rsc=5,
circle.cex=5,node.labs=T,var.labs=T,x.lab=NULL,y.lab=NULL,
line.stag=NULL,struct=NULL,cex.val=1,alpha.val=1,
circle.col='lightblue',pos.col='black',neg.col='grey',
bord.col='lightblue', max.sp = F,...){
require(scales)
#sanity checks
if('mlp' %in% class(mod.in)) warning('Bias layer not applicable for rsnns object')
@boyanangelov
boyanangelov / Spark+ipython_on_MacOS.md
Created February 29, 2016 20:38 — forked from ololobus/Spark+ipython_on_MacOS.md
Apache Spark installation + ipython notebook integration guide for Mac OS X

Apache Spark installation + ipython notebook integration guide for Mac OS X

Tested with Apache Spark 1.3.1, Python 2.7.9 and Java 1.8.0_45 + workaround for Spark 1.4.x from @enahwe.

Install Java Development Kit

Download and install it from oracle.com

@boyanangelov
boyanangelov / svmflag.py
Last active September 2, 2015 14:00 — forked from glamp/svmflag.py
Plotting SVM predictions using matplotlib and sklearn
import numpy as np
import pylab as pl
import pandas as pd
from sklearn import svm
from sklearn import linear_model
from sklearn import tree
from sklearn.metrics import confusion_matrix
@boyanangelov
boyanangelov / inference.r
Created August 25, 2015 09:57
Statistical inference function
function(y, x = NULL,
est = c("mean", "median", "proportion"),
success = NULL, order = NULL,
method = c("theoretical","simulation"),
type = c("ci","ht"),
alternative = c("less","greater","twosided"),
null = NULL,
boot_method = c("perc","se"),
conflevel = 0.95, siglevel = 0.05,
nsim = 10000, simdist = FALSE, seed = NULL,
@boyanangelov
boyanangelov / maps-ipython.py
Created August 18, 2015 20:20
Making maps in IPython
%pylab inline
from pylab import *
pylab.rcParams['figure.figsize'] = (8.0, 6.4)
from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
import numpy as np
map = Basemap(projection='ortho', lat_0=50, lon_0=-100,
resolution='l', area_thresh=1000.0)
@boyanangelov
boyanangelov / ds-training.md
Last active August 29, 2015 14:27 — forked from hadley/ds-training.md
My advise on what you need to do to become a data scientist...

If you were to give recommendations to your "little brother/sister" on things that they need to do to become a data scientist, what would those things be?

I think the "Data Science Venn Diagram" (http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram) is a great place to start. You need three things to be a good data scientist:

  • Statistical knowledge
  • Programming/hacking skills
  • Domain expertise

Statistical knowledge