Linear Regression - Revision history

BPeat at 02:48, 6 March 2024

2024-03-06T02:48:47Z

BPeat at 11:38, 17 August 2023

2023-08-17T11:38:45Z

BPeat at 01:16, 14 July 2023

2023-07-14T01:16:34Z

BPeat at 01:43, 6 July 2023

2023-07-06T01:43:17Z

BPeat at 18:09, 27 June 2023

2023-06-27T18:09:13Z

BPeat at 19:43, 17 June 2023

2023-06-17T19:43:54Z

BPeat at 02:01, 12 June 2023

2023-06-12T02:01:31Z

BPeat at 15:32, 4 June 2023

2023-06-04T15:32:28Z

BPeat: Text replacement - "http:" to "https:"

2023-03-29T04:17:33Z

Text replacement - "http:" to "https:"

BPeat at 14:47, 12 October 2020

2020-10-12T14:47:17Z

@@ Line 17: / Line 17: @@
 [https://www.google.com/search?q=Linear+Regression+machine+learning+ML ...Google search]
-* [[AI Solver]] ... [[Algorithms]] ... [[Algorithm Administration|Administration]] ... [[Model Search]] ... [[Discriminative vs. Generative]] ... [[Optimizer]] ... [[Train, Validate, and Test]]
+* [[AI Solver]] ... [[Algorithms]] ... [[Algorithm Administration|Administration]] ... [[Model Search]] ... [[Discriminative vs. Generative]] ... [[Train, Validate, and Test]]
 ** [[...predict values]]
 * [[Regression]] Analysis

@@ Line 23: / Line 23: @@
 * [https://medium.com/simple-ai/linear-regression-intro-to-machine-learning-6-6e320dbdaf06 Linear Regression — Intro To Machine Learning | Simple AI]
 * [https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regression Linear Regression | Microsoft]
-* [[Excel]] ... [[LangChain#Documents|Documents]] ... [[Database]] ... [[Graph]] ... [[LlamaIndex]]
+* [[Excel]] ... [[LangChain#Documents|Documents]] ... [[Database|Database; Vector & Relational]] ... [[Graph]] ... [[LlamaIndex]]
 * [[Logistic Regression (LR)]]
 * [https://www.analyticsvidhya.com/blog/2015/08/comprehensive-guide-regression/ 7 Types of Regression Techniques you should know! | Sunil Ray]

@@ Line 17: / Line 17: @@
 [https://www.google.com/search?q=Linear+Regression+machine+learning+ML ...Google search]
-* [[AI Solver]]
+* [[AI Solver]] ... [[Algorithms]] ... [[Algorithm Administration|Administration]] ... [[Model Search]] ... [[Discriminative vs. Generative]] ... [[Optimizer]] ... [[Train, Validate, and Test]]
 ** [[...predict values]]
 * [[Regression]] Analysis
 * [https://medium.com/simple-ai/linear-regression-intro-to-machine-learning-6-6e320dbdaf06 Linear Regression — Intro To Machine Learning | Simple AI]
 * [https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regression Linear Regression | Microsoft]
 * [[Excel]] ... [[LangChain#Documents|Documents]] ... [[Database]] ... [[Graph]] ... [[LlamaIndex]]
 * [[Logistic Regression (LR)]]
 * [https://www.analyticsvidhya.com/blog/2015/08/comprehensive-guide-regression/ 7 Types of Regression Techniques you should know! | Sunil Ray]

@@ Line 2: / Line 2: @@
 |title=PRIMO.ai
 |titlemode=append
-|keywords=artificial, intelligence, machine, learning, models, algorithms, data, singularity, moonshot, Tensorflow, Google, Nvidia, Microsoft, Azure, Amazon, AWS
+|keywords=ChatGPT, artificial, intelligence, machine, learning, GPT-4, GPT-5, NLP, NLG, NLC, NLU, models, data, singularity, moonshot, Sentience, AGI, Emergence, Moonshot, Explainable, TensorFlow, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Hugging Face, OpenAI, Tensorflow, OpenAI, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Meta, LLM, metaverse, assistants, agents, digital twin, IoT, Transhumanism, Immersive Reality, Generative AI, Conversational AI, Perplexity, Bing, You, Bard, Ernie, prompt Engineering LangChain, Video/Image, Vision, End-to-End Speech, Synthesize Speech, Speech Recognition, Stanford, MIT |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
 |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
 }}
 [https://www.youtube.com/results?search_query=Linear+Regression+artificial+intelligence YouTube search...]
@@ Line 10: / Line 19: @@
 * [[AI Solver]]
 ** [[...predict values]]
 * [[Regression]] Analysis
 * [https://medium.com/simple-ai/linear-regression-intro-to-machine-learning-6-6e320dbdaf06 Linear Regression — Intro To Machine Learning | Simple AI]

@@ Line 14: / Line 14: @@
 * [https://medium.com/simple-ai/linear-regression-intro-to-machine-learning-6-6e320dbdaf06 Linear Regression — Intro To Machine Learning | Simple AI]
 * [https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regression Linear Regression | Microsoft]
-* [[Excel]] ... [[LangChain#Documents|Documents]] ... [[Database]] ... [[Graph]] ... [[Algorithm Administration#AIOps/MLOps|AIOps/MLOps]] ... [[Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)|AIaaS/MLaaS]]
+* [[Excel]] ... [[LangChain#Documents|Documents]] ... [[Database]] ... [[Graph]] ... [[LlamaIndex]]
 * [[Math for Intelligence]] ... [[Finding Paul Revere]]
 * [[Logistic Regression (LR)]]

@@ Line 5: / Line 5: @@
 |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
 }}
-[http://www.youtube.com/results?search_query=Linear+Regression+artificial+intelligence YouTube search...]
+[https://www.youtube.com/results?search_query=Linear+Regression+artificial+intelligence YouTube search...]
-[http://www.google.com/search?q=Linear+Regression+machine+learning+ML ...Google search]
+[https://www.google.com/search?q=Linear+Regression+machine+learning+ML ...Google search]
 * [[AI Solver]]
@@ Line 12: / Line 12: @@
 * [[Capabilities]]
 * [[Regression]] Analysis
-* [http://medium.com/simple-ai/linear-regression-intro-to-machine-learning-6-6e320dbdaf06 Linear Regression — Intro To Machine Learning | Simple AI]
+* [https://medium.com/simple-ai/linear-regression-intro-to-machine-learning-6-6e320dbdaf06 Linear Regression — Intro To Machine Learning | Simple AI]
-* [http://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regression Linear Regression | Microsoft]
+* [https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regression Linear Regression | Microsoft]
 * [[Excel - Data Analysis]]
 * [[Math for Intelligence]]
 * [[Logistic Regression (LR)]]
-* [http://www.analyticsvidhya.com/blog/2015/08/comprehensive-guide-regression/ 7 Types of Regression Techniques you should know! | Sunil Ray]
+* [https://www.analyticsvidhya.com/blog/2015/08/comprehensive-guide-regression/ 7 Types of Regression Techniques you should know! | Sunil Ray]
-* [http://www.unite.ai/what-is-linear-regression/ What is Linear Regression? | Daniel Nelson - Unite.ai]
+* [https://www.unite.ai/what-is-linear-regression/ What is Linear Regression? | Daniel Nelson - Unite.ai]
 * [[Regularization]] to address [[Overfitting Challenge]]
-A method to find pattern with a “Best Fit Line” ( therefore, “Linear” get it ?) in your data.  [http://towardsdatascience.com/linear-regression-the-easier-way-6f941aa471ea Linear Regression: The Easier Way | Towards Data Science]
+A method to find pattern with a “Best Fit Line” ( therefore, “Linear” get it ?) in your data.  [https://towardsdatascience.com/linear-regression-the-easier-way-6f941aa471ea Linear Regression: The Easier Way | Towards Data Science]
 Linear regression is a common statistical method, which has been adopted in machine learning and enhanced with many new methods for fitting the line and measuring error. In the most basic sense, regression refers to prediction of a numeric target. Linear regression is still a good choice when you want a very simple model for a basic predictive task. Linear regression also tends to work well on high-dimensional, sparse data sets lacking complexity.
@@ Line 27: / Line 27: @@
 Linear Regression is similar to [[Logistic Regression (LR)]], but it is used when your target variable is continuous, which means it can take on essentially any numerical value. In fact, any model with a continuous target variable can be categorized as “regression.” An example of a continuous variable would be the selling price of a house. Linear regression is also very interpretable. The model equation contains coefficients for each variable, and these coefficients indicate how much the target variable changes for each small change in the independent variable (the x-variable). With the house prices example, this means that you could look at your regression equation and say something like “oh, this tells me that for every increase in 1ft² of house size (the x-variable), the selling price (the target variable) increases by $25.” [https://thenextweb.com/neural/2020/04/25/machine-learning-models-explained-to-a-five-year-old-syndication/ An explanation of machine learning models even you could understand | Megan Dibble - TNW]
-http://cdn-images-1.medium.com/max/640/1*eeIvlwkMNG1wSmj3FR6M2g.gif
+https://cdn-images-1.medium.com/max/640/1*eeIvlwkMNG1wSmj3FR6M2g.gif
-Linear Regression algorithm will use the data points to find the best fit line to model the data. A line can be represented by the equation, y = m*x + c where y is the dependent variable and x is the independent variable. Basic calculus theories are applied to find the values for m and c using the given data set.  Linear Regression has 2 types as Simple Linear Regression where only 1 independent variable is used and Multiple Linear Regression where multiple independent variables are defined. [http://towardsdatascience.com/10-machine-learning-algorithms-you-need-to-know-77fb0055fe0 10 Machine Learning Algorithms You need to Know | Sidath Asir @ Medium]
+Linear Regression algorithm will use the data points to find the best fit line to model the data. A line can be represented by the equation, y = m*x + c where y is the dependent variable and x is the independent variable. Basic calculus theories are applied to find the values for m and c using the given data set.  Linear Regression has 2 types as Simple Linear Regression where only 1 independent variable is used and Multiple Linear Regression where multiple independent variables are defined. [https://towardsdatascience.com/10-machine-learning-algorithms-you-need-to-know-77fb0055fe0 10 Machine Learning Algorithms You need to Know | Sidath Asir @ Medium]
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