VladimirNikiforov

awesome-machine-learning-interpretability

A curated list of awesome machine learning interpretability resources.

deep_learning_for_vision_systems

This repository accompanies the book "Deep Learning for Vision Systems".

java

Java scripts from different courses

Keras-GAN

Keras implementations of Generative Adversarial Networks.

linux

Shell scripts from course of Linux shell

netology-ds

Data Scientist Specialization in Netology

Neural_Networks_and_CV

R

Courses in R, Statistics and Data Analysis

Research-Computer-Vision

Implementations of computer vision concepts.

triplet-reid

Code for reproducing the results of our "In Defense of the Triplet Loss for Person Re-Identification" paper.

VladimirNikiforov/netology-ds

Data Scientist Specialization in Netology

VladimirNikiforov/java

Java scripts from different courses

VladimirNikiforov/R

Courses in R, Statistics and Data Analysis

VladimirNikiforov/assignment-computer-vision

Train imagenet neuralnet with TensorFlow and Docker

VladimirNikiforov/ImageAI

A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities

VladimirNikiforov/netology-dl

Course of Deep Learning

VladimirNikiforov/netology-ds-diploma

Diploma of Netology Data Scientist specialization

VladimirNikiforov/python_common

Python scripts from different courses

VladimirNikiforov/deep_learning_for_vision_systems

This repository accompanies the book "Deep Learning for Vision Systems".

VladimirNikiforov/Keras-GAN

Keras implementations of Generative Adversarial Networks.

VladimirNikiforov/Neural_Networks_and_CV

VladimirNikiforov/triplet-reid

Code for reproducing the results of our "In Defense of the Triplet Loss for Person Re-Identification" paper.

VladimirNikiforov/capstone_user_identification

User session classification in Python

VladimirNikiforov/deep-learning-lectures

VladimirNikiforov/Deep_Learning_AI

VladimirNikiforov/h2o-3

Open Source Fast Scalable Machine Learning Platform For Smarter Applications (Deep Learning, Gradient Boosting, Random Forest, Generalized Linear Modeling (Logistic Regression, Elastic Net), K-Means, PCA, Stacked Ensembles, Automatic Machine Learning (AutoML), ...)

VladimirNikiforov/incubator-singa

Mirror of Apache Singa (Incubating)

VladimirNikiforov/intro_to_llm_agents

Simple introduction to LLM Agents

VladimirNikiforov/kotaemon

An open-source RAG-based tool for chatting with your documents.

VladimirNikiforov/linux_shell

VladimirNikiforov/LLMs-from-scratch

Implementing a ChatGPT-like LLM in PyTorch from scratch, step by step

VladimirNikiforov/Machine-Learning-with-Python

Python code for common Machine Learning Algorithms

VladimirNikiforov/notebooks

Some sample IPython notebooks for scikit-learn

VladimirNikiforov/ods

Beginning of the course at OpenDataScience

VladimirNikiforov/python-machine-learning-book

The "Python Machine Learning (1st edition)" book code repository and info resource

VladimirNikiforov/PythonDataScienceHandbook

Python Data Science Handbook: full text in Jupyter Notebooks

VladimirNikiforov/Real-time-object-detection-using-yolov2-and-distance-estimation

Real-time Object detection using yolov2 and distance estimation of object from the camera lens.

VladimirNikiforov/statistics_in_python

VladimirNikiforov/tensor-house

A collection of reference machine learning and optimization models for enterprise operations: marketing, pricing, supply chain

VladimirNikiforov/transformer-explainer

Transformer Explained Visually: Learn How LLM Transformer Models Work with Interactive Visualization