Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

To know stats by heart

Curated list of notes, books and other resources for the student of Nepal College of Information and Technology(NCIT) - Pokhara University, Nepal

📊 Methods of Applied Statistics Course Textbook Repository

Probabilidad y variables aleatorias para ML con R y Python con los Drs R.Alberich y A.Mir

Migrated to Tungsteno https://github.com/TungstenHub

📈 Machine Learning from the perspective of a Statistician using R

Mathematical modeling and optimization of the game Old School Runescape.

This is based on my experience of how to prepare data science interviews.

Predictions with Markov Chains is a JS application that multiplies a probability vector with a transition matrix multiple times (n steps - user defined). On each step, the values from the resulting probability vectors are plotted on a chart. The resulting curves on the chart indicate the behavior of the system over n steps.

Udacity Data Analyst Nanodegree - Project III

Discrete Probability Detector (DPD) application uses an algorithm that transforms any sequence of symbols into a transition matrix. It is able to detect the number of states from the sequence and calculate the transition probabilities between these states. This version of DPD is made in JavaScript.

《概率论与数理统计》陈希孺，中国科学技术大学出版社

The current JS application is a detector that uses observation sequences to construct the transition matrices for two models, which are merged into a single log-likelihood matrix (LLM). A scanner can use this LLM to search for regions of interest inside a longer sequence called z (the target).

A Binomial Distribution Calculator with useful charts

HarvardX: PH125.3x | Data Science: Probability

A modern and portable SOCR web-app that demonstrates the concepts of statistical analysis such as resampling, randomization and probabilistic simulation.

A javascript simulation demonstrating the effect of position sizing on the outcomes of a series of bets.

These implementations make use of an algorithm called DPD (Discrete Probability Detector), that transforms any sequence of symbols into a transition matrix. DPD is able to detect the number of states from the sequence and calculate the transition probabilities between these states. This version of DPD is made in JavaScript, VBS and VB6.

Probabilidad clásica y muestreo aleatorio simple en R: función sample()