Ionel Miu's repositories
awesome-quantum-computing
A curated list of awesome quantum computing learning and developing resources.
1806
18.06 course at MIT
Interactive-RAG
Using MongoDB Atlas + ActionWeaver, we can build a user proxy agent that efficiently retrieves and ingests relevant information. This agent presents the data to the user in an interactive and customizable manner, enhancing the overall user experience.
mml-book.github.io
Companion webpage to the book "Mathematics For Machine Learning"
QuantumComputation_FPGAs
Emulating Quantum Circuits on FPGAs
MIT_OCW_Linear_Algebra_18_06
IPython notebooks on Gilbert Strang's MIT course on linear algebra (18.06)
DevOps_Books
Contribute to Open-Source
Learn-Quantum-Machine-Learning
Learn Quantum Machine Learning using pennylane framework
QCSim
Quantum computing simulator
node-red-contrib-quantum
Quantum computing functionality for Node-RED
mathematical-methods-in-deep-learning-ipython
Python code (in the form of Jupyter ipython notebooks) to support the book "Math and Architectures of Deep Learning" (Krishnendu Chaudhury with Ananya Ashok, Sujay Narumanchi, Devashish Shankar).
qNetVO
Simulate and optimize quantum communication networks using quantum computers.
awesome-quantum-machine-learning
Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web
physics-with-friends
Ideas and problems from Road to Reality
From-0-to-Research-Scientist-resources-guide
Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.
ISLR-python
An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code
polarization
If you are a computer scientist or a physicist aspiring to become a quantum computing scientist, this list is for you. The topics include: Quantum mechanics Quantum information processing Quantum computing Quantum information theory
book
Codelabs
Quantum-Mechanics---The-Theoretical-Minimum
Here are my solutions to problems. I also include my "class notes", at the bottom of the page. They fill in many details not made explicit in the book but which helped my understanding.The Notes include solutions to a few additional problems.
Data-Scientist-Books
Data-Scientist-Books (Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Long Short Term Memory, Generative Adversarial Network, Time Series Forecasting, Probability and Statistics, and more.)
MITx-6.86x-Machine-Learning
MITx 6.86x | Machine Learning with Python | From Linear Models to Deep Learning
ML
Machine Learning and Deep Learning Resources
DBDA-python
Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code
mitx-sds-resources
Supplemental resources for courses in the MITx MicroMasters Program in Statistics and Data Science
goquant
python based trading engine for equities and cryptocurrency
Simple-Binance-Trader
This is a simple trading bot for the binance exchange.
MITx_6.86x
Notes of MITx 6.86x - Machine Learning with Python: from Linear Models to Deep Learning
binance-trader
đź’° Cryptocurrency Trading Bot for Binance (Experimental)