-factorial-of-a-number-using-recursion

C programming

-fetching-data-from-web-scraping

-finding-square-roots

Python programming

-handwritten-digit-classification-using-ann-mnist-

In handwritten recognition digits, characters are given as input. The model can be recognized by the system. A simple artificial neural network (ANN) has an input layer, an output layer and some hidden layers between the input and output layer. CNN has a very similar architecture as ANN.

-heart-disease-prediction-using-machine-learning-with-python-

Machine Learning Projects

-how-to-check-if-an-array-contains-a-number-in-python

Python Programming

-loan-status-prediction-using-machine-learning-with-python

Machine Learning Project

-machine-learning-intern-hacklab-solutions-

-write-a-program-to-find-all-pairs-of-integers-whose-sum-is-equal-to-a-given-number

Python programming

.movie-recommendaton-system-using-machine-learning

Built a content based movie recommender system using cosine similarity, where the recommendations are based on the item metadata (i.e - movies, products, songs etc.) Contains the idea of a user liking an item, thereafter the other user gets recommended with the similar items.

.punjabi-word-detection-yolov7-

1st-and-future---player-contact-detection-detect-player-contacts-from-sensor-and-video-data

The goal of this competition is to detect external contact experienced by players during an NFL football game. You will use video and player tracking data to identify moments with contact to help improve player safety.

adaboost-algorithm

What is the AdaBoost Algorithm? AdaBoost also called Adaptive Boosting is a technique in Machine Learning used as an Ensemble Method. The most common algorithm used with AdaBoost is decision trees with one level that means with Decision trees with only 1 split. These trees are also called Decision Stumps.

adding-two-matrix-in-python

Python language

anomaly-detection

Anomaly detection is the process of identifying unexpected items or events in data sets, which differ from the norm. And anomaly detection is often applied on unlabeled data which is known as unsupervised anomaly detection.

assignment-leadzen.ai

avl-tree

Implementation Of AVL

bias---variance-tradeoff

In statistics and machine learning, the bias–variance tradeoff is the property of a model that the variance of the parameter estimated across samples can be reduced by increasing the bias in the estimated parameters.

binary-classification

This is the assignment solution for the datascience role of a Company. I have attempted a binary classification problem given the data, and have attempted feature selection, training (with validation) and presented the predictions.

binary-heap

Implementation Of Binary Heap

binary-tree

Creating Binary Tree Using Python List

binerization

Binarization is the process of dividing data into two groups and assigning one out. of two values to all the members of the same group. This is usually accomplished. by defining a threshold t and assigning the value 0 to all the data points below. the threshold and 1 to those above it.

bivariate-analysis

Bivariate analysis:- is performed to find the relationship between each variable in the dataset and the target variable of interest (or) using 2 variables and finding the relationship between them.

bracket-sequences

Python Programming

bst

Implementation of binary search tree

c-program-to-find-maximum-minimum-element-in-array-

C programming

c-program-to-find-reverse-of-array

C programming

car-price-prediction

In this Project, we will learn Linear Regression and real time challenges during implementation for a business problem.

chef-and-bulb-invention

Chef is trying to invent the light bulb that can run at room temperature without electricity. So he has N gases numbered from 0 to N−1 that he can use and he doesn't know which one of the N gases will work but we do know it. Now Chef has worked on multiple search algorithms to optimize search. For this project, he uses a modulo-based search algorithm that he invented himself. So first he chooses an integer K and selects all indices i in increasing order such that imodK=0 and test the gases on such indices, then all indices i in increasing order such that imodK=1, and test the gases on such indices, and so on. Given N, the index of the gas p that will work, and K, find after how much time will he be able to give Chefland a new invention assuming that testing 1 gas takes 1 day. For example, consider N=5,p=2 and K=3. On the 1st day, Chef tests gas numbered 0 because 0mod3=0. On the 2nd day, Chef tests gas numbered 3 because 3mod3=0. On the 3rd day, Chef tests gas numbered 1 because 1mod3=1. On the 4th day, Chef tests gas numbered 4 because 4mod3=1. On the 5th day, Chef tests gas numbered 2 because 2mod3=2. So after 5 days, Chef will be able to give Chefland a new invention

churn-prediction-using-ann-

Churn prediction means detecting which customers are likely to leave a service or to cancel a subscription to a service.