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2021-deep-learning-gift-course

I am offering 12 hours of deep learning lessons with TensorFlow 2 to all my followers on social networks who want to get into artificial intelligence in 2021.

ai-nanodegree-udacity

alx-low_level_programming

alx-system_engineering-devops

an-unexpectedly-large-count-of-trees-in-the-western-sahara-and-sahel

This repository contains the code for the paper "An unexpectedly large count of trees in the western Sahara and Sahel".

awesome-earthobservation-code

A curated list of awesome tools, tutorials, code, helpful projects, links, stuff about Earth Observation and Geospatial stuff!

awesome-gee

A curated list of Google Earth Engine resources

azure-ml-training

Repo for the Udacity's Microsoft Azure ML Training

books

A repository where I put all the books I have already read.

compagnon_utilisateur_r

A book on R programming. Only in french yet.

crop2ml

Repository for options to describe a model unit in a declarative way. Imperative representation will be specific for each modelling framework.

data-cleaning-and-feature-engineering-loan-data-

SuperLender is a local digital lending company, which prides itself in its effective use of credit risk models to deliver profitable and high-impact loan alternative. Its assessment approach is based on two main risk drivers of loan default prediction:. 1) willingness to pay and 2) ability to pay. Since not all customers pay back, the company invests in experienced data scientist to build robust models to effectively predict the odds of repayment. These two fundamental drivers need to be determined at the point of each application to allow the credit grantor to make a calculated decision based on repayment odds, which in turn determines if an applicant should get a loan, and if so - what the size, price and tenure of the offer will be. There are two types of risk models in general: New business risk, which would be used to assess the risk of application(s) associated with the first loan that he/she applies. The second is a repeat or behaviour risk model, in which case the customer has been a client and applies for a repeat loan. In the latter case - we will have additional performance on how he/she repaid their prior loans, which we can incorporate into our risk model. It is your job to predict if a loan was good or bad, i.e. accurately predict binary outcome variable, where Good is 1 and Bad is 0.

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.

datainsightprogram

Repository for DataInsight Program, ML project, Carbon Modelling etc

docs

TensorFlow documentation

ds-python-geospatial

Python for GIS and Geoscience - specialist course Doctoral schools of Ghent University

earthengine-py-examples

A collection of 300+ examples for using Earth Engine and the geemap Python package

earthengine-py-notebooks

A collection of 360+ Jupyter Python notebook examples for using Google Earth Engine with interactive mapping

fastbook

The fastai book, published as Jupyter Notebooks

feature-engineering-live-sessions

ferret

The Ferret program from NOAA/PMEL

fkb

A two-way deep learning bridge between Keras and Fortran

free-programming-books

:books: Freely available programming books

freemanpolys

geog-g489-589

Course notes for Spring 2019 GEOG-G489/589

getpointvaluesongee.ipynb

Extract pixel values in Google Earth Engine (GEE) for Fluxnet sites

hackathon_beopenit

Predict flight delay base on United States Department of Transportation datasets

hamoye_data_eng_program

Hamoye Data Science Internship

handson-ml2

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.

honeycode_awsrestart

HoneyCode Team Repo.