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acme-project

ACME project

apriori-algorithm

artificial-neural-network

atm-predictions

background-mathematics

I have included in my GitHub repo a section on Statistics which looks at distribution measurements, or, how the data is spread out. The other section is on Matrix Algebra and looks at eigenvectors and eigenvalues, important properties of matrices that are fundamental to PCA.

clustering

Fundamentals of Clustering

convolutional-neural-networks-tutorial

covid-19-

analysis of COVID-19 using data-science

covid-19-analysis

data-crawling

Data Crawling from Marketplaces

datagen

Generate two circles with different parameters.

decision_boundary_of_logistic_regression

decision boundary of logistic regression

joint-data-augmentation-and-network-optimization-for-text-recognition

knn-regression

KNN regression's fundamentals and parameters analysis

linear_algebra

Fundamentals of Linear Algebra for Machine Learning

linear_regression_

logistic_regression

intro to logistic regression

naive-bayes-theorem

natural-language-processing

Natural Language Processing using Python

neural-networks-and-deep-learning

optimise-complexity-of-combinatoric-algorithm

Optimise complexity of combinatoric algorithm problem solutions

optimization

polynomial_regression

fundamentals of polynomial regression

principal-component-analysis

PCA is a technique for reducing the dimensionality of such datasets, increasing interpretability but at the same time minimizing information loss.

random_walk_generator

recommendation-system

Recommendation-System with MovieLens Data

representation-with-a-feature-cross

In this exercise, you'll experiment with different ways to represent features.

ridge-regression

Ridge regressions are some of the simple techniques to reduce model complexity and prevent over-fitting which may result from simple linear regression.

sigmoid_function

how do plotting sigmoid fuction

spark-nlp-workshop

Public runnable examples of using John Snow Labs' NLP for Apache Spark.