ibrokhimsadikov Goto Github PK

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abd_society

abe

airbnb

app_abu

arm_interactive

awslambda-serverless

bigdataclass

can-money-buy-politics-

General Description The all candidate summary file contains one record including summary financial information for all candidates who raised or spent money during the period no matter when they are up for election. This file is similar to the current campaign summary file described above. This file is completely dependent upon summary information reported by the campaign itself. This means that the time period covered by this file may be more recent than for the current version of the post-cycle candidate summary file described below. During the primary election season the period covered may be different for candidates in different states. The cost of this timeliness, though, is that some of the information available here is less precise than for the post-cycle candidate summary file. For example, break-outs by special interest group code are not possible. When using the all candidates summary file you need to be aware of some possible double counting of activity. Some candidates have more then one committee authorized to raise and spend funds on their behalf. The activity reflected in this file represents the sum of those committees. If they transfer funds back and forth among each other, this activity would be counted twice. Information about “transfers from authorized committees” and “transfers to authorized committees” is included in the file and if there are values in both of these fields it is necessary to subtract these from total receipts and total disbursements to obtain a more accurate value for actual activity.

cloud-dataproc

Cloud Dataproc: Samples and Utils

cluster-k-k-means-dbsacan-hirarch

clustering-pca-

colab-test

collections

credit-risk-default

delivery

Building continuous delivery app on GCP using Flask

dockerhub

Continuous delivery app through docker

dockerproj

This is dockerworkflow

final-projecct

Instacart dashboard

firstwebsite

flexdashboard

NYC flights dashboard with interesting chernoff graph

information-retrieval-query-processing-inverted-index

linear-regression

Running running regression and KNN through python

machine-translation-ibm1

ml-regression-claasification

naive-vs-decesion-tree-python

This is hands on guide to execute scikit learn with python

ner-annotator

Named Entity Recognition (NER) Annotation tool for SpaCy. Generates Traning Data as a JSON which can be readily used.

new-credit-risk

Updated files

ngrams-nltk

using NLTK to predict the language

queen-city-hack

Queen City Hack-submission