nmuru

365-DataScience-MachineLearningModels

actornetwork

Clustering the network of actors on IMDb

AMP-Parkinson-Disease-Prediction

Kaggle competition notebooks submitted

continuous-delivery-cloud-native-java-apps-2423655

Continuous Delivery for Cloud Native Java Apps

data_science_ML_lessons_biology

Tutorials on data science/machine learning using Python with a life-science perspective. When I started learning programming and machine learning, most of the examples were from other fields like IT or business, so sometimes I found it difficult to apply those skills to biological problems. I help make data science and machine learning more relatable and practical to beginners, especially in my major biology by sharing the skills and knowledge I have acquired in data science and computation. I will do my best to use biological datasets as examples.

feature-engineering-for-machine-learning

Code repository for the online course Feature Engineering for Machine Learning

feature-selection-for-machine-learning

Code repository for the online course Feature Selection for Machine Learning

gitops-foundations-app-2892009

GitOps Foundations

gitops-foundations-env-2892009

GitOps Foundations

handson-ml3

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

nmuru/365-DataScience-MachineLearningModels

nmuru/actornetwork

Clustering the network of actors on IMDb

nmuru/AMP-Parkinson-Disease-Prediction

Kaggle competition notebooks submitted

nmuru/continuous-delivery-cloud-native-java-apps-2423655

Continuous Delivery for Cloud Native Java Apps

nmuru/data_science_ML_lessons_biology

Tutorials on data science/machine learning using Python with a life-science perspective. When I started learning programming and machine learning, most of the examples were from other fields like IT or business, so sometimes I found it difficult to apply those skills to biological problems. I help make data science and machine learning more relatable and practical to beginners, especially in my major biology by sharing the skills and knowledge I have acquired in data science and computation. I will do my best to use biological datasets as examples.

nmuru/feature-engineering-for-machine-learning

Code repository for the online course Feature Engineering for Machine Learning

nmuru/feature-selection-for-machine-learning

Code repository for the online course Feature Selection for Machine Learning

nmuru/gitops-foundations-app-2892009

GitOps Foundations

nmuru/gitops-foundations-env-2892009

GitOps Foundations

nmuru/handson-ml3

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

nmuru/HelloNm

nmuru/Kaggle-Competitions---ICR-Identifying-Age-Related-Conditions

nmuru/Kaggle-Competitions---Parkinson-Gait-Prediction

nmuru/Kaggle-Competitions---Predict-Student-Performance-from-Game-Play

nmuru/Kaggle-Competitions--Google-American-Sign-Language-Fingerspelling-Recognition

nmuru/Kaggle-Competitions--LLM-Detect-AI-Generated-Text

nmuru/Kaggle-Competitions-House-Prices-Advanced-Regression-Techniques

nmuru/Kaggle-Competitions-Kaggle---LLM-Science-Exam

nmuru/LinAlgCourse-nm

Python and MATLAB code for online linear algebra course

nmuru/low_code_machine_learning_pycaret_workshop_2022

This workshop was done as a part of the 1729 conference organized by Fractal Analytics and Analytics Vidhya. Key content covered was hands-on notebooks leveraging PyCaret to compare, build, tune, evaluate and interpret machine learning models

nmuru/ML-foundations

Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science

nmuru/Project-on-linear-regression-with-Rshiny-dashboard

Leslie Salt Data Set In 1968, the city of Mountain View, California, began the necessary legal proceedings to acquire a parcel of land owned by the Leslie Sal Company. The Leslie property contained 246.8 acres and was located right on the San Francisco Bay. The land had been used for salt evaporation and had an elevation of exactly sea level. However, the property was diked so that the waters from the bay park were kept out. The city of Mountain View intended to fill the property and use it for a city park. Ultimately,it fell into the courts to determine a fair market value for the property. Appraisers were hired, but what made the processes difficult was that there were few sales of byland property and none of them corresponded exactly to the characteristics of the Leslie property. The experts involved decided to build a regression model to better understand the factors that might influence market valuation. They collected data on 31 byland properties that were sold during the previous 10 years. In addition to the transaction price for each property, they collected data oina large number of other factors, including size, time of sale, elevation, location, and access to sewers. A listing of these data, including only those variables deemed relevant for this exercise. A description of the variables is provided below. Variable name Description Price Sales price in $000 per acre County San Mateo=0, Santa Clara =1 Size Size of the property in acres Elevation Average Elevation in foot above sea level Sewer Distance (in feet) to nearest sewer connection Date Date of sale counting backward from current time (in months) Flood Subject to flooding by tidal action =1; otherwise =0 Distance Distance in miles from Leslie Property (in almost all cases, this is toward San Francisco Discuss and Answer the following questions: 1. What is the nature of each of the variables? Which variable is dependent variable and what are the independent variables in the model? 2. Check whether the variables require any transformation individually 3. Set up a regression equation, run the model and discuss your results

nmuru/python-hw

nmuru/pyyhon-hw

nmuru/tableau365

nmuru/TabPy

Execute Python code on the fly and display results in Tableau visualizations:

nmuru/tensorflow-deep-learning

All course materials for the Zero to Mastery Deep Learning with TensorFlow course.

nmuru/tfc-guide-example

Example Terraform configuration