Bola Lamidi's repositories

data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

License:NOASSERTIONStargazers:0Issues:0Issues:0

Dash-by-Plotly

Interactive data analytics

Stargazers:0Issues:0Issues:0

flask-admin-boilerplate

Flask Admin Boilerplate with MongoDB

License:MITStargazers:0Issues:0Issues:0

plotlydash-flask-tutorial

📊📉 Embed Plotly Dash into your Flask applications.

Stargazers:0Issues:0Issues:0

Grokking-Deep-Learning

this repository accompanies the book "Grokking Deep Learning"

Stargazers:0Issues:0Issues:0
Language:TypeScriptStargazers:0Issues:0Issues:0

Introduction-to-NLP

Lectures for Udemy - INLP

Stargazers:0Issues:0Issues:0
Language:HTMLStargazers:0Issues:0Issues:0

Breast-Cancer-Classification-with-Support-Vector-Machine

In this study, my task is to classify tumors into malignant or benign using features obtained from several cell images.

Language:Jupyter NotebookStargazers:14Issues:0Issues:0
Language:Jupyter NotebookStargazers:1Issues:0Issues:0

resource-datasets

A resource for those exploring data analysis machine learning.

Language:RStargazers:0Issues:0Issues:0

US-Mass-Shootings-Analysis

Mass Shootings in the United States of America (1966-2017) The US has witnessed 398 mass shootings in last 50 years that resulted in 1,996 deaths and 2,488 injured. The latest and the worst mass shooting of November 5, 2017 killed 58 and injured 515 so far. The number of people injured in this attack is more than the number of people injured in all mass shootings of 2015 and 2016 combined. The average number of mass shootings per year is 7 for the last 50 years that would claim 39 lives and 48 injured per year.

Language:Jupyter NotebookStargazers:2Issues:0Issues:0

BigMart-Sales-Prediction-

The aim is to build a predictive model and find out the sales of each product at a particular store. Using this model, BigMart will try to understand the properties of products and stores which play a key role in increasing sales.

Language:Jupyter NotebookStargazers:1Issues:0Issues:0

House-Prices-Advanced-Regression-Techniques

Kaggle: House Prices Competition

Language:Jupyter NotebookStargazers:1Issues:0Issues:0

Building-a-movie-recommender-Engine-

Creating a Recommendation Engine

Language:Jupyter NotebookStargazers:1Issues:0Issues:0

NLP

The aim is to build a prediction model that will accurately classify which texts are spam

Language:Jupyter NotebookStargazers:1Issues:0Issues:0

dialectdetect

Deep Neural Network that classifies a person's native language based on their accent

Language:Jupyter NotebookStargazers:0Issues:0Issues:0
Stargazers:0Issues:0Issues:0

pydata-book

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

Language:Jupyter NotebookLicense:NOASSERTIONStargazers:0Issues:0Issues:0

Kickstarter-Predictive-Analysis

Predicting the success of Kickstarter campaigns

Language:Jupyter NotebookStargazers:2Issues:0Issues:0

Web-Scrapping-Project

Scraping Chubby Grub website to create a DataFrame.

Language:Jupyter NotebookStargazers:0Issues:0Issues:0

Boston-Housing-Price-Prediction

Used Linear Regression Model to predict Housing Price using the Boston Housing Dataset

Language:Jupyter NotebookStargazers:0Issues:0Issues:0

Titanic-Project

Kaggle competition

Language:Jupyter NotebookStargazers:0Issues:0Issues:0

PythonDataScienceHandbook

Jupyter Notebooks for the Python Data Science Handbook

Language:Jupyter NotebookLicense:MITStargazers:0Issues:0Issues:0

scientific_python_cheat_sheet

simple overview of python, numpy, scipy, matplotlib functions that are useful for scientific work

Language:HTMLLicense:CC-BY-4.0Stargazers:0Issues:0Issues:0

pandas-cookbook

Recipes for using Python's pandas library

Language:Jupyter NotebookStargazers:0Issues:0Issues:0

spark-movie-lens

An on-line movie recommender using Spark, Python Flask, and the MovieLens dataset

Language:Jupyter NotebookLicense:NOASSERTIONStargazers:0Issues:0Issues:0

DAT4

General Assembly's Data Science course in Washington, DC

Language:Jupyter NotebookStargazers:0Issues:0Issues:0