Hi Entrepreneurship and Statistics Enthusiasts, I welcome you to this story.
The story starts with the Alert !!
It’s A Kaggle Story :). The Dataset used for this story can be found here. After this alert, I am more comfortable in starting the story since I have given the credit to the Dataset Master ☺.
So Let’s Begin with the story plot:-
So Presenting answers to your obvious curiosity 😃
What is Entrepreneurship?
Entrepreneurship is the creation or extraction of value. With this definition, entrepreneurship is viewed as change, generally entailing risk beyond what is normally encountered in starting…
GPUs or graphics processing units is a processor that is good at handling computations.
Ok!! but the same things are done by CPUs or (Central Processing Unit), about which we have been learning from our school days as the “brain of the computer”.
So an important question what differentiates GPUs from CPUs?
To answer this question lets tweak our earlier definition a bit -
GPUs are good at handling “specialized computations” and CPUs are good at handling “general computations”.
Now another question what is an example of special and general computation? …
Let’s Dive into an amazing programming question to sharpen your problem-solving skills.
I guess you are :)
Here is the Question-
Given an array
nums of n integers, are there elements a, b, c in
nums such that a + b + c = 0? Find all unique triplets in the array which gives the sum of zero.
Notice that the solution set must not contain duplicate triplets.
Input: nums = [-1,0,1,2,-1,-4]
Input: nums = 
Input: nums = 
0 <= nums.length <= 3000
This Triplet is one of the most confusing things in Python Programming and one of the most asked questions in interviews. Let’s clear this confusion one by one in detail:-
An iterator is an object that contains a countable number of values.
Technically, in Python, an iterator is an object which implements the iterator protocol, which consists of the methods __iter__() and __next__().
This creates an iterator.
This return the first element i.e 3
This returns the next element i.e 4 and so on.
An example of how to create your own iterator:-
Let’s create an…
One of the key steps in building a machine learning model is to estimate its performance on data that the model hasn’t seen before.Let’s assume that we fit our model on a training dataset and use the same data to estimate how well it performs on new data.The model can suffer from underfitting (high bias) if the model is too simple, or it can overfit the training data (high variance) if the model is too complex for the underlying training data.To find an acceptable bias-variance tradeoff, we need to evaluate our model carefully.
The common cross-validation techniques holdout cross-validation and…