Hey Guys,

Interviewing.io is a fantastic resource I wanted to share with you all.

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Mastering algorithms on LeetCode and system design on SystemsExpert is great, but they don’t prepare you for the pressure and stress that comes from an actual interview setting.

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Tech Snippets

• Detecting Financial Fraud using GANs

  • Existing approaches to identify financial fraud rely on databases of human-engineered rules that match suspicious patterns in financial transactions

  • Swedbank (one of Sweden’s largest banks) has developed an approach of using GANs for anomaly detection.

  • Here’s a survey paper on using GANs for anomaly detection.

• Functional Programming Design Patterns with Scott Wlaschin

  • Wlaschin talks about

    • The core principles of functional programming design

    • Functions as parameters

    • Monads

    • Maps

    • Monoids

Interview Question

Write a function to randomly generate a set of m integers from an array of size n.

Each element must have an equal probability of being chosen.

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Previous Solution

As a refresher, here’s the last question

Given two straight line segments (represented as a start point and an end point), compute the point of intersection (if it exists).

Example

Input - ([(-8.7, -24.8), (3.46, 23.84)], [(-13.76, -29.4),(6.2, 20.5)])

Output - (-3.3333, -3.3333)

Solution

This question mostly revolves around basic geometry concepts and your ability to express that in code.

Remember that a line is an infinitely long collection of points extending in two opposite directions. A line segment is just a part of that line. It has a set start point and end point.

First, we should break down the possible scenarios for our line segments.

1. The line segments have the same slope

   1. The line segments intersect - Our two line segments are part of the same line and they’re overlapping (or they’re the same line segment).

   2. The line segments do not intersect

      1. the line segments are part of different, parallel lines

      2. the line segments are part of the same line but do not intersect

2. The line segments have different slopes - our two line segments are part of lines that have different slopes, so those two lines have to intersect. The question is whether the point of intersection of those two lines is within our line segments.

   1. The line segments intersect - The point of intersection of those two lines is within our line segments.

   2. The line segments do not intersect - the point of intersection of those two lines is not within our line segments.

So, these are our possible cases.

Now, we have to come up with a way to represent our Line Segments.

We’ll create a class to do this for us. We can also bundle some functionality into our class so we can reuse those functions when calculating the intersection point of two line segments.

Here’s the interface for our Line Segment class.

class LineSegment

constructor(startPoint, endPoint)

calculateSlope()

calculateYIntercept()

isPointOnSegment(point)

isPointOnSegment will take in a point and return True/False depending on whether the point is on our line segment.

Now, we can implement our getLineSegmentIntersection function.

We first create objects for our Line Segments.

Then, we compare the slopes.

If the slopes are equal, then we compare the y-intercepts of both line segments.

If the y-intercepts are equal, that means both line segments are segments of the same line.

In that case, we return true if the lines overlap (we check this with isPointOnSegment for the start and end points of line segment 2 for line segment 1).

If the slopes aren’t equal, then we need to check if the intersection point of the two lines (the lines underlying our line segments) is within both line segments.

We first find the intersection point of the two lines using some basic algebra.

Then, we use isPointOnSegment to check if our intersection point is on line segment 1 and line segment 2.

Remember that we’re working with floating point numbers here! This is extremely important when we’re checking for equality.

We use a relative tolerance of 0.01 when checking for equality.

Here’s the Python 3 code!

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