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Bastin Robin BastinRobin

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BastinRobin /
Last active August 29, 2022 10:39
HandOn - Cyber Security For Managers - B1

We have been provided with the dataset from XYZ Labs Network Intrusion Logs, Our network protection classifier was able to detect Anamoly vs Normal requests. But as a cyber security expert, your duty is to find out the following details.

  • Which services has highest anamoly detected.
  • Which protocal has highest anamoly detected
  • How many private services had anamoly and which type of protocol used.
  • Does total request counts has any correlation with anamoly.
  • Which are most important variables which contributes to an anamoly.

Download Dataset:

BastinRobin /
Last active March 20, 2022 07:04
U.S. International Air Passenger and Freight Statistics

The data comes from the U.S. International Air Passenger and Freight Statistics Report. As part of the T-100 program, USDOT receives traffic reports of US and international airlines operating to and from US airports. There are two datasets available:

Departures: Data on all flights between US gateways and non-US gateways, irrespective of origin and destination. Each observation provides information on a specific airline for a pair of airports, one in the US and the other outside. Three main columns record the number of flights: Scheduled, Charter, and Total. Passengers: Data on the total number of passengers for each month and year between a pair of airports, as serviced by a particular airline.

U.S. International Air Passenger and Freight data are confidential for a period of 6 months, after which it can be released. As a result, quarterly reports and the year to date/calendar year raw data files available here will always lag by two quarters. Questions that can be answered with data

  • Top 10 busiest airp
BastinRobin / main.go
Created February 25, 2022 15:18
Ambee API
View main.go
package main
import (
BastinRobin / Python Plan
Created December 23, 2021 15:51
Simple Python Class
View Python Plan
Python Learning Plan
- How to install python on Mac
- Install VSCode editor on Mac
- How to Run python code using terminal
- Variable and constants
- Scope of Variable
- Variable data types
- Integer {0,1,2,1000}
- Float { Decimal - 10.1, 2.01 }
- Boolean (True, False)
BastinRobin /
Created December 4, 2021 09:29 — forked from patik/
How to squash commits in git

Squashing Git Commits

The easy and flexible way

This method avoids merge conflicts if you have periodically pulled master into your branch. It also gives you the opportunity to squash into more than 1 commit, or to re-arrange your code into completely different commits (e.g. if you ended up working on three different features but the commits were not consecutive).

Note: You cannot use this method if you intend to open a pull request to merge your feature branch. This method requires committing directly to master.

Switch to the master branch and make sure you are up to date:

BastinRobin /
Created October 21, 2021 09:52
Covid 19
  1. Which district has more cases?
  2. Total survived cases across country?
  3. Geographical pattern of pandemic spread?
  4. Rate of survival across districts?
  5. What is the recovery rate across countries, districts, state?
  6. Rate of new cases across districts?
  7. Total active cases in India?
  8. Datewise new cases in India?
  9. To understand the relation between new and death cases
BastinRobin /
Created May 19, 2021 07:17
Hierarichal Clustering

Implementation of Hierarichal Clustering (Agglomeration Cluster)

Hierarchical clustering algorithms group similar objects into groups called clusters. There are two types of hierarchical clustering algorithms:

  • Agglomerative — Bottom up approach. Start with many small clusters and merge them together to create bigger clusters.
  • Divisive — Top down approach. Start with a single cluster than break it up into smaller clusters.

Create a Hierarical clustering and experiment the following tutorial

BastinRobin /
Created May 12, 2021 08:21
Ensemble Technique

Implement Ensemble Techniques On Given Dataste

Dataset This given dataset consists of the following datapoints

  • id - unique ID for excerpt
  • url_legal - URL of source - this is blank in the test set.
  • license - license of source material - this is blank in the test set.
  • excerpt - text to predict reading ease of
  • target - reading ease
BastinRobin /
Created May 5, 2021 08:36
Implementation Of K-Mean To Analyse Crime in US

# K-Means Clustering - U.S. Crime Data

We'll use k-means to discover clusters in a data set using unsupervised learning. The original data can be found here

From the Unified Crime Reporting Statistics and under the collaboration of the U.S. Department of Justice and the Federal Bureau of Investigation information crime statistics are available for public review. The following data set has information on the crime rates and totals for states across the United States for a wide range of years. The crime reports are divided into two main categories: property and violent crime. Property crime refers to burglary, larceny, and motor related crime while violent crime refers to assault, murder, rape, and robbery. These reports go from 1960 to 2012.

The analysis consists of the following steps.

  • I. Importing necessary libraries and downloading the data
BastinRobin /
Last active March 24, 2021 04:48
Implement Naive Bayes

Implement Naive Bayes Classifier

Naive Bayes methods are a set of supervised learning algorithms based on applying Bayes' theorem with the “naive” assumption of conditional independence between every pair of features given the value of the class variable.

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Use the above dataframe as reference and build a Naive Bayes Classifier using python. Follow the guidelines.

  1. Build a production ready classifier following the API interfaces.