ipynb-notebook
There are 43 repositories under ipynb-notebook topic.
leonvanbokhorst/NoteBooks-Statistics-and-MachineLearning
Jupyter Notebooks from the old UnsupervisedLearning.com (RIP) machine learning and statistics blog
Norod/my-colab-experiments
A repository for sharing ipynb's of my experiments with ML. Some notebooks are 'old' by now and might no longer work 'out of the box'.
jirutka/ipynb2html
Convert Jupyter (IPython) Notebooks to static HTML
OmmmmooooO/wavelet101
A simple tutorial of wavelet, STFT and FFT
mkearney/rmd2jupyter
Convert Rmd (rmarkdown) to ipynb (Jupyter notebook)
nishi1612/Modelling-and-Simulation
CS302 Modelling and Simulation Weekly Assignments in python based on modelling different systems - SARS, Malaria, SIR
isweluiz/data-science
Python for data science
MeitarBach/nba-individual-predictions-lstm
NBA players individual performance perdictions using Neural Networks. Comparison between LSTM and Feed Forward Architectures. Created by Meitar Bach, Mai Elenberg and Lior Ben-Ami
s-valent/jupyterlab-app
An app for macOS that launches and displays jupyter lab. No need to keep terminal open for that anymore!
Anyesh/KNN-notebook
Jupyter Notebook for KNN Algorithm.
diptangsu/Python-decorators
Where and how to use decorators in python.
Elijas/movie-review-sentiment-polarity-classifier
Training a classifier to differentiate between positive and negative movie review sentences in the "sentence polarity dataset v1.0"
ortizfram/Time-Series-analysis-101
Python · Store Sales - Time Series Forecasting
sanjayan1734/19CSE305-Sem-V-term-project
19CSE305 Term project
semereab-merry/Machine-learning-projects
Collection of data science projects. Each sector takes to kaggle page where you can find the codes along with explanations and analysis.
Bluelord/Kaggle_Courses
Kaggle learn course tutorial and exercises notebook
Dwijraj/Natural-Language-Processing
Beginning with NLP
ps0305/Python-3-Bootcamp
Python BootCamp
sflender/deep-learning-test
Exploring deep learning on Cooley
tottaz/torbjorns-iphyton-notebooks
This is a collection of sample iPhyton Notebooks, these can be used with Google Cloud Datalab
GrindelfP/borrowers-investigation
An analysis of a dataset of borrowers, EDA and identification of dependences between debts and other features.
kiwi6185/webCrawlers
【爬虫】B站自学：https://www.bilibili.com/video/BV1ha4y1H7sx/
Kryp6405/Dog-Breed-Classification
This Dog Breed Classification model employs TensorFlow 2.0 and Transfer Learning with ResNet50v2 to accurately identify 70 different dog breeds from images, demonstrating the power of deep learning in image classification tasks.
prash030/Table1_baseline-characteristics
This repository contains a python notebook that creates Table-1: baseline characteristics with p-values comparing two groups. Greatly helpful for clinical and biological studies. Can be used for manuscipts.
rohitkadu/web-scraper-python
Web Scraper using Python
GrindelfP/linear-regression-study
Examples of linear regression.
joeywhelan/search-scoring
Demonstration of use of SCORE_FIELD with Redis Search scoring
Kimulegen/matematica-aplicada
Ejercicios de Matemática Aplicada 2024_2_PV_MAT2121_24220631_PCT
neerajcodes888/A-Novel-Used-Car-Price-Prediction-Model-Based-on-LinDenoise
Welcome to the LinDenoise Repository! LinDenoise offers a smart solution for cleaning noisy data in regression tasks. Integrated seamlessly within the widely-used scikit-learn framework, it effortlessly enhances data quality while improving predictive accuracy
OshaPandey/Text_Extraction
In this project, we will be working on extracting text from images. After extracting the text we will apply some basic functions of opencv on that text to enhance it and to get more accurate results. This project will be very useful as it will save time and effort of typing from an image.
rnddave/python-like-a-boss
This is where I stash my Python study material.
sahal-mulki/learning-pytorch
My .IPYNB notebooks made while learning PyTorch.
suhail25/Hotel-Booking-Analysis
Analyzed the cancelling of booking of hotels and summarized insights to the Hotel Manager to increase profit by 30%. Demonstrated data exploration, cleaning, analysis using Python and its libraries: pandas, seaborn, matplot. Documented the results in PDF report: reduced cancellation by 30% and releasing discounts for 10 days in a month.
yashuv/NumPy-for-Data-Science
A well structured practical deep dive into functional programming in NumPy.
yasmeensayeed/ML-project-prediction-dataset-salary-using-SVM-model
ML-project-prediction-dataset-salary-using-SVM-model