KNKalinin

Adv_Fin_ML_Exercises

Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]

Book-PYTHON-FOR-FINANCE

Jupyter Notebooks and codes for Python for Finance (2nd ed., O'Reilly) by Yves Hilpisch.

Data-Science--Cheat-Sheet

Cheat Sheets

Deep-Learning-For-Hackers

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

deep-rl-class

This repo contains the syllabus of the Hugging Face Deep Reinforcement Learning Course.

equity-portfolio-prediction

Geron_handson-ml3

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.

Grokking-Deep-Learning

this repository accompanies my forthcoming book "Grokking Deep Learning"

How-to-Win-a-Data-Science-Competition

How to Win a Data Science Competition: Learn from Top Kagglers

KNKalinin/How-to-Win-a-Data-Science-Competition

How to Win a Data Science Competition: Learn from Top Kagglers

KNKalinin/Adv_Fin_ML_Exercises

Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]

KNKalinin/Book-PYTHON-FOR-FINANCE

Jupyter Notebooks and codes for Python for Finance (2nd ed., O'Reilly) by Yves Hilpisch.

KNKalinin/Data-Science--Cheat-Sheet

Cheat Sheets

KNKalinin/Deep-Learning-For-Hackers

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

KNKalinin/deep-rl-class

This repo contains the syllabus of the Hugging Face Deep Reinforcement Learning Course.

KNKalinin/equity-portfolio-prediction

KNKalinin/Geron_handson-ml3

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.

KNKalinin/Grokking-Deep-Learning

this repository accompanies my forthcoming book "Grokking Deep Learning"

KNKalinin/Indicators

Collection of indicators that I used in my strategies.

KNKalinin/Machine-Learning-for-Algorithmic-Trading-Second-Edition

Code and resources for Machine Learning for Algorithmic Trading, 2nd edition.

KNKalinin/Maintenance-in-manufacturing-systemsmaintsim

Simulation of maintenance in manufacturing systems

KNKalinin/Mastering-Python-for-Finance-Second-Edition

Mastering Python for Finance – Second Edition, published by Packt

KNKalinin/multi-echelon-inventory-optimization

multi-echelon inventory optimization with SimPy, SciPy, sklearn, and RBFOpt

KNKalinin/predictive-maintenance

Data Wrangling, EDA, Feature Engineering, Model Selection, Regression, Binary and Multi-class Classification (Python, scikit-learn)

KNKalinin/quantopian-research_public

Quantitative research and educational materials

KNKalinin/Quantra_ml-trading-book

This repository contains the python codes as well as data files which have been included in the ML for Trading ebook

KNKalinin/RetailReplenishement

CRP Code

KNKalinin/stock_screener

Picking stocks through various screening methods. Focus on Northern Europe.

KNKalinin/StockPredictionAI

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

KNKalinin/Supply-Chain-and-Logistics-Analytics

KNKalinin/Supply_Chain_Analytics

KNKalinin/Symon_dlcourse_ai

Материалы курса Deep Learning на пальцах

KNKalinin/Technical_Analysis_and_Feature_Engineering

Feature Engineering and Feature Importance of Machine Learning in Financial Market.

KNKalinin/TensorFlow-Tutorials

TensorFlow Tutorials with YouTube Videos

KNKalinin/ThinkDigitalSignakP

Think DSP: Digital Signal Processing in Python, by Allen B. Downey.

KNKalinin/YNDX-mashinnoye-obucheniye

:books: Специализация «Машинное обучение и анализ данных»