Image Processing with Python — Blob Detection using Scikit-Image
How to identify and segregate specific blobs in your image
scipy
Image Processing with Python — Blurring and Sharpening for Beginners
How do you apply convolution kernels to colored images?
BFGS in a Nutshell: An Introduction to Quasi-Newton Methods
Demystifying the inner workings of BFGS optimization
Essential Math for Data Science: Information Theory
Entropy, cross-entropy, log loss, and KL divergence
Represent your Geospatial Data using Folium
As a part of the Data Science community, Geospatial data is one of the most crucial kind of data to work with. The applications are as…
Introduction to PyMC3: A Python package for probabilistic programming
An introduction to PyMC3 through a concrete example
EM Algorithm
Mathematical Background and Example
Financial Independence — Simulating ODEs With Python
Use Python to set your path towards it.
Basic Curve Fitting of Scientific Data with Python
A basic guide to using Python to fit non-linear functions to experimental data points
SICP in Python
Berkeley CS61A Textbook
Getting Started with Spectral Clustering - Dr. Juan Camilo Orduz
Partial Correlation Vs. Conditional Mutual Information
Finding relationships between different variables/ features in a dataset during a data analysis task is one of the key and fundemental…
Getting started with the NVIDIA Jetson Nano - PyImageSearch
In this tutorial, you will learn how to get started with your NVIDIA Jetson Nano, including installing Keras + TensorFlow, accessing the camera, and performing image classification and object detection.
Over 150 of the Best Machine Learning, NLP, and Python Tutorials I’ve Found
By popular demand, I’ve updated this article with the latest tutorials from the past 12 months. Check it out here
ctgk/PRML: PRML algorithms implemented in Python
PRML algorithms implemented in Python.
Bayesian Bandits explained simply - MLWhiz
There are multiple ways to doing the same thing in Pandas, and that might make it troublesome for the beginner user.This post is about handling most of the data manipulation cases in Python using a straightforward, simple, and matter of fact way.
[N] scikit-optimize 0.7 release
Scikit-Optimize, or skopt, is a simple and efficient library to minimize (very) expensive and noisy black-box functions. It implements several…
SciPy 1.0: fundamental algorithms for scientific computing in Python | Natu
Nature Methods - This Perspective describes the development and capabilities of SciPy 1.0, an open source scientific computing library for the Python programming language.
P-value Explained Simply for Data Scientists
This post is about various evaluation metrics and how and when to use them.
Welcome to PyTorch Tutorials — PyTorch Tutorials 1.3.0 documentation
A Brief Introduction to PySpark - Towards Data Science
PySpark is a great language for performing exploratory data analysis at scale, building machine learning pipelines, and creating ETLs for…
Basic Linear Algebra for Deep Learning | Built In
Basic linear algebra can have a surprising influence on deep learning and machine learning. Learn what linear algebra is and how to use it.
Keras Mask R-CNN - PyImageSearch
In this tutorial you will learn how to use Keras, Mask R-CNN, and Deep Learning for instance segmentation (both with and without a GPU).
Advanced NLP with spaCy · A free online course
spaCy is a modern Python library for industrial-strength Natural Language Processing. In this free and interactive online course, you'll learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.
yzhao062/pyod: A Python Toolbox for Scalable Outlier Detection (Anomaly Det
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques - yzhao062/pyod
Working efficiently with JupyterLab Notebooks
Being in the data science domain for quite some years, I have seen good Jupyter notebooks but also a lot of ugly. Notebooks can have the perfect balance between text, code and visualisations but how often do your notebooks rather get messy and incomprehensible after a while?…
Forecasting in Python with Prophet | Reports - Mode
A guided walkthrough of how to use the Prophet python library to solve a common forecasting problem.
scikit-surprise 1.0.5 : Python Package Index
An easy-to-use library for recommender systems.
LouieYang/deep-photo-styletransfer-tf: Tensorflow (Python API) implementati
Tensorflow (Python API) implementation of Deep Photo Style Transfer - LouieYang/deep-photo-styletransfer-tf
Eecs227at
AutonomousDrivingCookbook/AirSimE2EDeepLearning at master · Microsoft/Auton
Scenarios, tutorials and demos for Autonomous Driving - microsoft/AutonomousDrivingCookbook
Understanding Feature Engineering (Part 3) — Traditional Methods for Text D
Traditional strategies for taming unstructured, textual data
Understanding Feature Engineering (Part 1) — Continuous Numeric Data
Strategies for working with continuous, numerical data
Gensim: topic modelling for humans
Efficient topic modelling in Python
How to use detectron facebooks free platform for object detection 9d41e170bbcb
Numba: High-Performance Python with CUDA Acceleration
Numba is an open-source Python compiler from Anaconda that can compile Python code for high-performance execution on CUDA-capable GPUs or multicore CPUs.
Why is Kullback-Leibler divergence not a distance?
The Kullback-Leibler divergence between two probability distributions is sometimes called a "distance," but it's not. Here's why.