Pinned Repositories
admission_data
ATM_logging
This Python code demonstrates how to use the logging module to create a simple bank account management system.
book_recommender
In this project, I explore the process of building and fine-tuning a recommender system using the Surprise library in Python.
Boosting
By utilizing a census dataset in conjunction with boosting algorithms, I predict whether an individual's income exceeds $50,000.
cifar10_cnn
Training a Convolutional Neural Network (CNN) to classify images from the CIFAR-10 database. The CIFAR-10 dataset consists of small color images grouped into ten classes, including objects like airplanes, automobiles, birds, cats, and more.
hb_lighthouse_report_in_R
This R-code will show you how to recreate the typical lighthouse/sawtooth report content and structure of a hierarchical Bayes logistic regression analysis using data collected with choice-based conjoint design
NFL_Stats
"Python web scraping for NFL stats from the official website for the 2023 season, covering multiple categories."
Presidential_Vocabulary
In this project, I leverage the power of natural language processing (NLP) and word embeddings to uncover the linguistic patterns, common themes, and unique insights hidden within the inaugural addresses of U.S. presidents, spanning from 1789 to 2017.
Sentiment_RNN
This project focuses on building a sentiment analysis model using Recurrent Neural Networks (RNNs) for classifying movie reviews as either positive or negative
tennis_ace
A U.S. Tennis Player Performance Analysis project using Python, Pandas, Matplotlib, Seaborn, and scikit-learn. It explores tennis player data, visualizes correlations, and builds regression models to predict player performance.
MarcLinderGit's Repositories
MarcLinderGit/NFL_Stats
"Python web scraping for NFL stats from the official website for the 2023 season, covering multiple categories."
MarcLinderGit/cifar10_cnn
Training a Convolutional Neural Network (CNN) to classify images from the CIFAR-10 database. The CIFAR-10 dataset consists of small color images grouped into ten classes, including objects like airplanes, automobiles, birds, cats, and more.
MarcLinderGit/Presidential_Vocabulary
In this project, I leverage the power of natural language processing (NLP) and word embeddings to uncover the linguistic patterns, common themes, and unique insights hidden within the inaugural addresses of U.S. presidents, spanning from 1789 to 2017.
MarcLinderGit/Sentiment_RNN
This project focuses on building a sentiment analysis model using Recurrent Neural Networks (RNNs) for classifying movie reviews as either positive or negative
MarcLinderGit/tennis_ace
A U.S. Tennis Player Performance Analysis project using Python, Pandas, Matplotlib, Seaborn, and scikit-learn. It explores tennis player data, visualizes correlations, and builds regression models to predict player performance.
MarcLinderGit/admission_data
MarcLinderGit/ATM_logging
This Python code demonstrates how to use the logging module to create a simple bank account management system.
MarcLinderGit/Boosting
By utilizing a census dataset in conjunction with boosting algorithms, I predict whether an individual's income exceeds $50,000.
MarcLinderGit/breast_cancer
Simple K Nearest Neighbors Classification using sklearn Dataset
MarcLinderGit/broncos_restaurant_bot
I employ techniques such as tf-idf scoring, word embedding models, and custom user-defined functions to create an interactive chatbot capable of answering a wide range of questions from restaurant diners.
MarcLinderGit/cats_transfer
I use an image classifier in comination with transfer learning with pre-trained neural networks. The main goal is to leverage the knowledge learned by networks trained on the extensive ImageNet dataset to achieve impressive accuracy in distinguishing between cat and dog images.
MarcLinderGit/census_income_lr
Creating a logistic regression model to classify income (>50K or <=50K) using census data from the '94 Census database.
MarcLinderGit/Concurrent_Programming
This Python script provides examples of different approaches to calculate the average of multiple lists using sequential, asynchronous, multithreading, and multiprocessing techniques.
MarcLinderGit/ESPN_Stats
MarcLinderGit/flags
This project aims to develop a decision tree model to classify countries' continent ("landmass regions") based on flag characteristics. The primary goal is to predict whether a country belongs to either Europe or Oceania based on flag attributes.
MarcLinderGit/galaxies
In this project, I employ Convolutional Neural Networks (CNNs) to classify galaxies based on image data from the Galaxy Zoo dataset.
MarcLinderGit/generative_chatbot
MarcLinderGit/heart_failure
MarcLinderGit/Hierarchical_Classes
This Python project demonstrates the use of hierarchical classes and object-oriented programming (OOP).
MarcLinderGit/life_expectancy
MarcLinderGit/life_expectancy_gdp
I'll explore the captivating link between GDP and life expectancy across six countries. Using data from the World Health Organization and World Bank, I'll analyze, visualize, and discover insights that reveal the fascinating connections between these factors.
MarcLinderGit/Machine_Translations
This repository contains Python code for implementing a Neural Machine Translation (NMT) system.
MarcLinderGit/MarcLinderGit
MarcLinderGit/ML_Pipelines
This project is focused on building a classification model to predict the survival status of patients with bone marrow disease while streamlining the data preprocessing and model building process through pipelines.
MarcLinderGit/mnist_mlp
Training a Multi-Layer Perceptron (MLP, i.e., modern feedforward artificial neural network, consisting of fully connected neurons) to classify images from the MNIST database hand-written digit database.
MarcLinderGit/multi_chatbot
The Multi-Topic Chat Bot is a simple Python program that engages in conversations with users on various topics, including football, movies, and music. The bot initiates conversations, responds to user queries, and provides information related to the selected topic.
MarcLinderGit/NFL_Stats_ESPN
MarcLinderGit/Surf_Shop
This project employs unit testing to ensure the functionality and reliability of a Python-based surf shop application. It includes tests for adding surfboards, applying discounts, and handling exceptions to maintain a robust and error-resistant shopping experience.
MarcLinderGit/us_medical_insurance_cost
I'll analyze a US medical insurance cost dataset using data techniques to uncover patterns, explore influences on charges, and provide insights for decision-making. Utilizing Python and libraries like NumPy, pandas, Matplotlib, Seaborn, and scikit-learn for effective data analysis.
MarcLinderGit/X-Rays