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-banking-credit_risk_model

Credit risk modeling is the place where data science and fintech meet. It is one of the most important activities conducted in a bank, with the most attention since the recession. At present, it is the only comprehensive credit risk modeling course in Python available online – taking you from preprocessing, through probability of default (PD), loss given default (LGD) and exposure at default (EAD) modeling, all the way to calculating expected loss (EL).

-banking-finance-_quantitative-risk-management-in-python

🎇🖥️💻📜🏪🏢🏢🏢🏢

-banking_finance-garch-models-in-python

Volatility is an essential concept in finance, which is why GARCH models in Python are a popular choice for forecasting changes in variance, specifically when working with time-series data that are time-dependant.

-banking_finance-portfolio-risk-management

evaluate basic portfolio risk and returns . fully automate portfolio (Banking )construction and management processes. Discover what factors are driving portfolio returns, construct market-cap weighted equity portfolios,forecast and hedge market risk via scenario generation.

a-visual-history-of-nobel-prize-winners

Datacamp Project ....... can see by https://projects.datacamp.com/projects/441

adam-adagard-rmsprob

implement algorthims (adam&adagard&RMSprob) by Dataset

analyzing-police-activity-with-pandas

Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior.

bike_rental_predication_kagglecompatition_ml

cairo_cairo-governorate_nlp_task

develop a model that takes a text of an address and verify if this address is in Cairo governorate or not with a confidence threshold of your prediction.

car-crashes-severity-prediction_kagglecompetition

it's required to predict the Severity of a car crash given info about the crash, e.g., location. This is the getting started notebook.

computer-vision

convert-xml-to-json-in-python

we will look into the method to convert XML to JSON in Python. The JSON format is simpler to read and write than XML format; its compact style and lightweight also improve system performance, especially in RESTful APIs. As JSON is better than XML in many aspects, it is used as a replacement to XML in many fields.

credit-risk-modeling

data_visualization-

interactive Dashboard

deep_learning

Introduction to Neural Networks with Scikit-Learn

dr.-semmelweis-and-the-discovery-of-handwashing

This is Dr. Ignaz Semmelweis, a Hungarian physician born in 1818 and active at the Vienna General Hospital. If Dr. Semmelweis looks troubled it's probably because he's thinking about childbed fever: A deadly disease affecting women that just have given birth. He is thinking about it because in the early 1840s at the Vienna General Hospital as many as 10% of the women giving birth die from it. He is thinking about it because he knows the cause of childbed fever: It's the contaminated hands of the doctors delivering the babies. And they won't listen to him and wash their hands! In this notebook, we're going to reanalyze the data that made Semmelweis discover the importance of handwashing. Let's start by looking at the data that made Semmelweis realize that something was wrong with the procedures at Vienna General Hospital.

dry-beans-classification

Have a set of features extracted from the shape of the beans in images and it's required to predict the type of each bean. There are 7 bean types in the dataset.

emotion-detetction-for-nlp-

games

turtle to draw lines

graduation_project_iti_credit_risk_model-

how-read-dataset-from-kaggle-in-colab-by-api-

implementation-gd-gradient-decent-

investigating-netflix-movies-and-guest-stars-in-the-office

to discover if Netflix’s movies are getting shorter over time and which guest stars appear in the most popular episode of "The Office",

llm-tutorial-code-

machine-learning-in-java

Java project for machine learning and data exploration of "Wuzzuf_Jobs" dataset using smile library and KMeans unsupervised algorithm.

machine_learning_1

momentum---nag

natural-language-processing-nlp-

* FAKE NEWS * libraries such as NLTK *the foundation to process and parse text as you move forward

netflix-recommending-_recomendersystem

Build recommendation engine. grips with the two most common systems, collaborative filtering and content-based filtering. Next, measure similarities like the Jaccard distance and cosine similarity, and how to evaluate the quality of recommendations on test data using the root mean square error (RMSE). built movie recommendation engine that are systems for any industry.

nlp-101-iti-course

NLP course for ITI AI-Pro track