From d59f5a11c2144db7894097256a16bb74284a8aa0 Mon Sep 17 00:00:00 2001 From: Albert <87888006+MustCodeAl@users.noreply.github.com> Date: Wed, 7 Aug 2024 21:57:05 -0500 Subject: [PATCH 1/3] Update probability.rst add placeholders for probablility --- docs/probability.rst | 100 +++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 100 insertions(+) diff --git a/docs/probability.rst b/docs/probability.rst index 89bd780..d35a065 100644 --- a/docs/probability.rst +++ b/docs/probability.rst @@ -12,6 +12,106 @@ This cheatsheet is a 10-page reference in probability that covers a semester's w The cheatsheet is based off of Harvard's introductory probability course, Stat 110. It is co-authored by former Stat 110 Teaching Fellow William Chen and Stat 110 Professor Joe Blitzstein. + +**Probability** is a number between 0 and 1 that tells how likely something is to happen. If something is sure to happen, the probability is 1. +If something can never happen, the probability is 0. We write the probability of something as P(thing), where "thing" is what we're talking about. + + +Events +====== +An event is represented as a group (set) of all possible results. This group is a part (subset) of all possible outcomes. + + + +The total probability of the outcomes in X must be 1, i.e., P(X) = 1. +Since the events in probability theory are sets, we can manipulate them using +standard set operations: +• The **complement A¯ means ”A does not happen”. For example, when +throwing a dice, the complement of A = {2,4,6} is A¯ = {1,3,5}. +• The union A ∪ B means ”A or B happen”. For example, the union of +A = {2,5} and B = {4,5,6} is A ∪B = {2,4,5,6}. +• The intersection A ∩B means ”A and B happen”. For example, the intersection of A = {2,5} and B = {4,5,6} is A ∩B = {5}. + + +Complement +---------- + + + +Union +----- + + + +Conditional probability +----------------------- + + + +Intersection +------------ + + + +Random variables +================ + + +A **random variable** is a value that is generated by a random process. For +example, when throwing two dice, a possible random variable is + + + +Expected value +-------------- + + +Distributions +------------- + + + + + + + + +Deviation from the Mean +======================== + + +Markov’s Theorem +---------------- + + +Properties of Variance +---------------------- + + + +Estimation by Random Sampling +----------------------------- + + +Randomized algorithms +===================== + +Order statistics +---------------- + +Verifying matrix multiplication +------------------------------- + + +Graph coloring +-------------- + + + + + + + Links ------- From b32cd0f5df174aea8d9bc7a9956f9bfa08477e1d Mon Sep 17 00:00:00 2001 From: Albert <87888006+MustCodeAl@users.noreply.github.com> Date: Wed, 7 Aug 2024 22:12:31 -0500 Subject: [PATCH 2/3] Update libraries.rst add candle and juice library --- docs/libraries.rst | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/docs/libraries.rst b/docs/libraries.rst index fc2c892..af62efd 100644 --- a/docs/libraries.rst +++ b/docs/libraries.rst @@ -893,8 +893,10 @@ Rust .. rubric:: General-Purpose Machine Learning +- `candle `__ - Candle is a minimalist ML framework for Rust with a focus on performance (including GPU support) and ease of use. - `deeplearn-rs `__ - deeplearn-rs provides simple networks that use matrix multiplication, addition, and ReLU under the MIT license. -- `rustlearn `__ - a machine learning framework featuring logistic regression, support vector machines, decision trees and random forests. +- `juice `__ - Juice is a open Machine Learning Framework for hackers to build classical, deep or hybrid machine learning applications. +- `rustlearn `__ - a machine learningr framework featuring logistic regression, support vector machines, decision trees and random forests. - `rusty-machine `__ - a pure-rust machine learning library. - `leaf](https://github.com/autumnai/leaf) - open source framework for machine intelligence, sharing concepts from TensorFlow and Caffe. Available under the MIT license. [**[Deprecated]** `__ - `RustNN `__ - RustNN is a feedforward neural network library. From 496672c003e94b59d8e2313511fa4edab42dc3ad Mon Sep 17 00:00:00 2001 From: Albert <87888006+MustCodeAl@users.noreply.github.com> Date: Wed, 7 Aug 2024 22:16:05 -0500 Subject: [PATCH 3/3] Discard changes to docs/probability.rst --- docs/probability.rst | 100 ------------------------------------------- 1 file changed, 100 deletions(-) diff --git a/docs/probability.rst b/docs/probability.rst index d35a065..89bd780 100644 --- a/docs/probability.rst +++ b/docs/probability.rst @@ -12,106 +12,6 @@ This cheatsheet is a 10-page reference in probability that covers a semester's w The cheatsheet is based off of Harvard's introductory probability course, Stat 110. It is co-authored by former Stat 110 Teaching Fellow William Chen and Stat 110 Professor Joe Blitzstein. - -**Probability** is a number between 0 and 1 that tells how likely something is to happen. If something is sure to happen, the probability is 1. -If something can never happen, the probability is 0. We write the probability of something as P(thing), where "thing" is what we're talking about. - - -Events -====== -An event is represented as a group (set) of all possible results. This group is a part (subset) of all possible outcomes. - - - -The total probability of the outcomes in X must be 1, i.e., P(X) = 1. -Since the events in probability theory are sets, we can manipulate them using -standard set operations: -• The **complement A¯ means ”A does not happen”. For example, when -throwing a dice, the complement of A = {2,4,6} is A¯ = {1,3,5}. -• The union A ∪ B means ”A or B happen”. For example, the union of -A = {2,5} and B = {4,5,6} is A ∪B = {2,4,5,6}. -• The intersection A ∩B means ”A and B happen”. For example, the intersection of A = {2,5} and B = {4,5,6} is A ∩B = {5}. - - -Complement ----------- - - - -Union ------ - - - -Conditional probability ------------------------ - - - -Intersection ------------- - - - -Random variables -================ - - -A **random variable** is a value that is generated by a random process. For -example, when throwing two dice, a possible random variable is - - - -Expected value --------------- - - -Distributions -------------- - - - - - - - - -Deviation from the Mean -======================== - - -Markov’s Theorem ----------------- - - -Properties of Variance ----------------------- - - - -Estimation by Random Sampling ------------------------------ - - -Randomized algorithms -===================== - -Order statistics ----------------- - -Verifying matrix multiplication -------------------------------- - - -Graph coloring --------------- - - - - - - - Links -------