yadhavaramanan Goto Github PK

-implement-linear-regression-on-student-s-data-

array-implementation-of-queue

array-implemetation-of-stack-using-c-

asynchronous-file-operations-using-the-fs-module-in-node.js

create-dataset-using-python

cricket_club_management_system

In this project just including sql queries like insert, update, delete, select to adding, updating,showing, deleting players details which is stored in database.

data-structure--fifo

game-using-python-using-pygame-

graphs-in-data-structure-using-c-

hash-techniques-in-data-structure-using-c-

image-classification-using-cnn-model-from-tensorflow

image-classification-using-opencv

implementation-of-avl-tree

implementation-of-bankers-algorithm

implementation-of-cpu-scheduling-algorithms

implementing-q-learning-with-linear-function

n this Q-learning implementation, a grid world environment is defined with 16 states, and agents can take 4 possible actions: up, down, left, and right. The goal is to reach state 15. The Q-table, initialized with zeros, serves as a memory to store Q-values for state-action pairs.

index.github.io

kmeans

knn-_algorithm

The K-Nearest Neighbors (KNN) algorithm is a supervised machine learning method employed to tackle classification and regression problems. Evelyn Fix and Joseph Hodges developed this algorithm in 1951, which was subsequently expanded by Thomas Cover.

load_iris_dataset

The Iris dataset was used in R.A. Fisher's classic 1936 paper, The Use of Multiple Measurements in Taxonomic Problems, and can also be found on the UCI Machine Learning Repository.

my-portfolio

naive_bayes_algorithm

Naïve Bayes is part of a family of generative learning algorithms, meaning that it seeks to model the distribution of inputs of a given class or category. Unlike discriminative classifiers, like logistic regression, it does not learn which features are most important to differentiate between classes.

object_recognization_pre-trained_model

policy-gradient

Policy gradient methods are a type of reinforcement learning techniques that rely upon optimizing parametrized policies with respect to the expected return (long-term cumulative reward) by gradient descent. In the off-policy algorithm, actions are sample using behaviour policy and separate target policy is used to optimise for.

pre-booking-for-food-in-hotals

Pre-booking food in hotels is a convenient way to ensure you have meals ready at your preferred times during your stay.Some hotels require pre-payment for meals, while others may allow you to pay during your stay, so make sure you understand the payment terms.

programs-using-the--exec--calls

real-time-examples-in-java

searching-algorithms-in-c-

semi-supervised-classifier

small-project