Added a number of links from the @virgili0 repo (thanks to @clone95) …

…across a number of sections and sub-sections in this repo
vishweshs4 · Jan 19, 2020 · 4fc717a · 4fc717a
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diff --git a/Programming-in-Python.md b/Programming-in-Python.md
@@ -16,6 +16,7 @@
 
 ## Basics / learning
 
+- [Python Fundamentals](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/fundamentals/python-fundamentals/python-fundamentals.md)
 - [Lists, Tuples, Dictionaries, Conditionals, Loops, etc...](https://lnkd.in/gWRbc3J)
 - [Data Structures & Algorithms](https://lnkd.in/gYKnJWN)
 - [NumPy Arrays](https://lnkd.in/geeFePh)

diff --git a/README-details.md b/README-details.md
@@ -16,6 +16,7 @@
 - [Notebooks](#notebooks)
 - [Models](#models)
 - [Articles, papers, code, data, courses](#articles-papers-code-data-courses)
+- [Other Tools](#other-tools)
 - [Presentations](#presentations)
 - [Best Practices](#best-practices)
 - [Cheatsheets](#cheatsheets)
@@ -28,7 +29,8 @@
 
 ### Artificial Intelligence
 
-See [Artificial Intelligence](./details/artificial-intelligence.md)
+- [Demystification of the key concepts of Artificial Intelligence and Machine Learning](https://github.com/virgili0/Virgilio/blob/master/serving/paradiso/demystification-ai-ml-dl/demystification-ai-ml-dl.md)
+- See [Artificial Intelligence](./details/artificial-intelligence.md)
 
 ### Automation
 
@@ -123,6 +125,10 @@ See [Notebooks](./notebooks/README.md#notebooks)
 
 See [Articles, papers, code, data, courses](./details/articles-papers-code-data-courses.md)
 
+### Other Tools
+
+See [Other Tools](./things-to-know.md#other-tools)
+
 ### Presentations
 
 - [NLP presentations](./natural-language-processing/README.md#presentations)

diff --git a/data/README.md b/data/README.md
@@ -7,6 +7,7 @@ The question to ask ourselves: _Do we know our data...?_
 ---
 
 - [Ethics / altruistic motives](./README.md#ethics--altruistic-motives)
+- [Data Science](./README.md#data-science)
 - [Datasets and sources of raw data](./README.md#datasets-and-sources-of-raw-data)
 - [Data Exploratory Analysis](./README.md#data-exploratory-analysis)
 - [Data preparation](./README.md#data-preparation)
@@ -37,6 +38,14 @@ The question to ask ourselves: _Do we know our data...?_
 
 See [Ethics / altruistic motives](../README-details.md#ethics--altruistic-motives)
 
+## Data Science
+
+- [The Data Science Process](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/fundamentals/the-data-science-process/the-data-science-process.md)
+  - [Frame The Problem](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/define-the-scope-and-ask-questions/frame-the-problem/frame-the-problem.md)
+  - [Usage and Integration](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/define-the-scope-and-ask-questions/usage-and-integration/usage-and-integration.md)
+  - [Starting a Data Project](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/define-the-scope-and-ask-questions/starting-a-data-project/starting-a-data-project.md)
+  - [WorkSpace Setup and Cloud Computing](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/define-the-scope-and-ask-questions/workspace-setup-and-cloud-computing/workspace-setup-and-cloud-computing.md)
+
 ## Datasets and sources of raw data
 
 See [Datasets](./datasets.md)
@@ -47,7 +56,8 @@ See [Data Exploratory Analysis](./data-exploratory-analysis.md)
 
 ## Data preparation
 
-See [Data preparation](./data-preparation.md)
+- [Data preparation](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/collect-and-prepare-data/data-preparation/data-preparation.md)
+- See [Data preparation](./data-preparation.md)
 
 ## Data Generation
 
@@ -71,7 +81,8 @@ See [Statistics.md](statistics.md#statistics)
 
 ## Visualisation
 
-See [Visualisation](../details/visualisation.md#visualisation)
+- [Data Visualization](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/collect-and-prepare-data/data-visualization/data-visualization.md)
+- See [Visualisation](../details/visualisation.md#visualisation)
 
 ## Common mistakes when training models (data related)
 

diff --git a/details/articles-papers-code-data-courses.md b/details/articles-papers-code-data-courses.md
@@ -1,5 +1,7 @@
 # Articles, papers, code, data, courses
 
+  - [State-of-Art Papers Explained](https://github.com/virgili0/Virgilio/blob/master/serving/inferno/research/sota-papers/sota-papers.md)
+  - [Zotero: a tool to help in the manage collection of papers](https://github.com/virgili0/Virgilio/blob/master/serving/inferno/research/zotero/zotero.md)
   - [Papers, code, data by Yaz](https://github.com/yazdotai/paper-code-data)
   - [Awesome AI Papers by Yaz (empty atm)](https://github.com/yazdotai/awesome-ai-papers)
   - [Papers and code](https://paperswithcode.com)

diff --git a/details/java-jvm.md b/details/java-jvm.md
@@ -103,12 +103,21 @@ MLPMNist using DL4J: [![MLPMNist using DL4J](https://img.shields.io/docker/pulls
 
 ## Data Science 
 
+- [The Data Science Process](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/fundamentals/the-data-science-process/the-data-science-process.md)
+   - Also see [Data Science](../data/README.md#data-science)
 - [Data Science for Java Developers](https://www.oreilly.com/library/view/data-science-with/9781491934104/ch01.html)
 - [Virgilio - Your new Mentor for Data Science E-Learning](https://github.com/clone95/Virgilio)
 - [Introduction to Data Science](https://www.youtube.com/watch?v=HEN6FBRuElE) | [Other Data Science Stuff related videos](https://www.youtube.com/channel/UCTe3bYxbzhstIRuIuGQz7UQ)
 
 ## Machine Learning
 
+- [Demystification of the key concepts of Artificial Intelligence and Machine Learning](https://github.com/virgili0/Virgilio/blob/master/serving/paradiso/demystification-ai-ml-dl/demystification-ai-ml-dl.md)
+- [What do you need for ML?](https://github.com/virgili0/Virgilio/blob/master/serving/paradiso/what-do-you-need-for-ml/what-do-you-need-for-ml.md)
+- [Do you really need ML?](https://github.com/virgili0/Virgilio/blob/master/serving/paradiso/do-you-really-need-ml/do-you-really-need-ml.md)
+- [ML use cases](https://github.com/virgili0/Virgilio/blob/master/serving/paradiso/use-cases/use-cases.md)
+- [Introduction to ML](https://github.com/virgili0/Virgilio/blob/master/serving/paradiso/introduction-to-ml/introduction-to-ml.md)
+- [Machine Learning Theory](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/select-and-train-machine-learning-models/machine-learning-theory/machine-learning-theory.md)
+- [Machine Learning Study Path](https://github.com/virgili0/Virgilio/blob/master/LearningPaths/Machine%20Learning%20Engineer%20Career%20Path)
 - [ML for Java Developers](https://www.itworld.com/article/3224505/application-development/machine-learning-for-java-developers.html)
 - [Java ML Dev Videos on YouTube: Naive Bayes w/ JAVA - Tutorial 01](https://www.youtube.com/watch?v=mrP4CyW4tKA&frags=pl%2Cwn)
 - Java ML Framework: [1](https://github.com/datumbox/datumbox-framework) [2](http://blog.datumbox.com/developing-a-naive-bayes-text-classifier-in-java/)
@@ -124,6 +133,7 @@ MLPMNist using DL4J: [![MLPMNist using DL4J](https://img.shields.io/docker/pulls
 
 ### Deep learning
 
+  - [Deep Learning Theory](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/select-and-train-machine-learning-models/deep-learning-theory/deep-learning-theory.md)
   - [JFocus: Deep learning with Java](https://www.jfokus.se/jfokus17/preso/Deep-Learning-on-Java-tutorial.pdf) | [Video](https://www.youtube.com/watch?v=-hgAp470F-M) |([Tweet](https://twitter.com/juanantoniobm/status/832000819918733312))
   - [Understanding Machine Learning Algorithms with DL4J](https://skymind.ai/wiki/machine-learning-algorithms) ([Tweet](https://twitter.com/java/status/1077947895691673600))
   - [DL4J: Deep Learning for Java](https://deeplearning4j.org/) | [Docs/Guide](https://deeplearning4j.org/docs/latest/) | [Quickstart](https://deeplearning4j.org/docs/latest/deeplearning4j-quickstart) | [Tutorial](https://deeplearning4j.org/tutorials/setup) | [Roadmap for Beginners](https://deeplearning4j.org/docs/latest/deeplearning4j-beginners) | [DL4J Eclipse GitHub](https://github.com/eclipse/deeplearning4j) | DL4J Examples: [GitHub](https://github.com/deeplearning4j/dl4j-examples) o [Semantic site](https://semantive.com/deep-learning-examples/) o [Examples Tour](https://deeplearning4j.org/docs/latest/deeplearning4j-examples-tour)| [Setup Environment](https://www.tutorialkart.com/machine-learning/setup-environment-for-deep-learning-with-deeplearning4j/) | [Using DL4J](https://www.quora.com/How-do-I-use-deep-learning-in-Java) | Support: [gitter.im](https://gitter.im/deeplearning4j/deeplearning4j/) o [gitter guidelines](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/GITTER_GUIDELINES.md) o [GitHub Issues](https://github.com/deeplearning4j/deeplearning4j/issues) o [Stackoverflow](https://stackoverflow.com/search?tab=newest&q=deeplearning4j)

diff --git a/details/julia-python-and-r.md b/details/julia-python-and-r.md
@@ -63,15 +63,17 @@
   - [What is Computer vision?](https://machinelearningmastery.com/what-is-computer-vision/)
   - [Main topics to be covered (Basic outline)](https://www.pyimagesearch.com/start-here/)
   - [Introduction to CV](https://blog.algorithmia.com/introduction-to-computer-vision)
+  - [Another: Introduction to CV](https://github.com/virgili0/Virgilio/blob/master/serving/inferno/computer-vision/introduction-to-computer-vision/introduction-to-computer-vision.ipynb)
 
   ### Image Processing
 
   - [Digital Image Processing Basics](https://www.geeksforgeeks.org/digital-image-processing-basics/)
   - [Theory for Image Processing](http://web.ipac.caltech.edu/staff/fmasci/home/astro_refs/Digital_Image_Processing_2ndEd.pdf)
+  - [Object Instance Segmentation](https://github.com/virgili0/Virgilio/blob/master/serving/inferno/computer-vision/object-instance-segmentation/object-instance-segmentation.ipynb)
+  - [Object Tracking](https://github.com/virgili0/Virgilio/blob/master/serving/inferno/computer-vision/object-tracking/object-tracking.ipynb)
   - See [Image Processing](../courses.md#image-processing) in [Courses](../courses.md)
 
   ### OpenCV and tutorials
-
   - [Documentation and examples for each topic](https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_imgproc/py_table_of_contents_imgproc/py_table_of_contents_imgproc.html)
 
   ### Courses
@@ -94,6 +96,8 @@
 
   ## Data Science
 
+  - [The Data Science Process](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/fundamentals/the-data-science-process/the-data-science-process.md)
+     - Also see [Data Science](../data/README.md#data-science)
   - [Data science intro for math/phys background by Poitr Migdal](https://p.migdal.pl/2016/03/15/data-science-intro-for-math-phys-background.html)
   - [What I do or: science to data science by Poitr Migdal](https://p.migdal.pl/2015/12/14/sci-to-data-sci.html)
   - [T. Cormen, C. Leiserson, R. Rivest and C. Stein, Introduction to Algorithms](https://en.wikipedia.org/wiki/Introduction_to_Algorithms)
@@ -103,6 +107,13 @@
 
   ## Machine Learning
 
+  - [Demystification of the key concepts of Artificial Intelligence and Machine Learning](https://github.com/virgili0/Virgilio/blob/master/serving/paradiso/demystification-ai-ml-dl/demystification-ai-ml-dl.md)
+  - [What do you need for ML?](https://github.com/virgili0/Virgilio/blob/master/serving/paradiso/what-do-you-need-for-ml/what-do-you-need-for-ml.md)
+  - [Do you really need ML?](https://github.com/virgili0/Virgilio/blob/master/serving/paradiso/do-you-really-need-ml/do-you-really-need-ml.md)
+  - [ML use cases](https://github.com/virgili0/Virgilio/blob/master/serving/paradiso/use-cases/use-cases.md)
+  - [Introduction to ML](https://github.com/virgili0/Virgilio/blob/master/serving/paradiso/introduction-to-ml/introduction-to-ml.md)
+  - [Machine Learning Theory](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/select-and-train-machine-learning-models/machine-learning-theory/machine-learning-theory.md)
+  - [Machine Learning Study Path](https://github.com/virgili0/Virgilio/blob/master/LearningPaths/Machine%20Learning%20Engineer%20Career%20Path)
   - [A curated list of awesome Machine Learning frameworks, libraries and software](https://github.com/josephmisiti/awesome-machine-learning)
   - [Top ML repos](https://github.com/yazdotai/top-machine-learning)
   - [Hands on ML](https://github.com/ageron/handson-ml)
@@ -148,6 +159,7 @@
 
   ### Deep Learning
 
+   - [Deep Learning Theory](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/select-and-train-machine-learning-models/deep-learning-theory/deep-learning-theory.md)
    - [FREE! Deep learning book online - by Ian Goodfellow and Yoshua Bengio and Aaron Courville](http://www.deeplearningbook.org/)
    - [A curated list of awesome Deep Learning tutorials, projects and communities](https://github.com/josephmisiti/awesome-deep-learning)
    - [Deep learning library featuring a higher-level API for TensorFlow](https://github.com/tflearn/tflearn)

diff --git a/details/maths-stats-probability.md b/details/maths-stats-probability.md
@@ -2,13 +2,15 @@
 
 ## Mathematics
 
+- [Math Fundamentals](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/fundamentals/math-fundamentals/math-fundamentals.md)
 - [Mathematics for Machine Learning](https://mml-book.github.io/book/mml-book.pdf)
 - [Topic-wise notes: maths & stats](https://www.ctanujit.org/lecture-notes.html)
 - [Number Representation Systems Explained in One Picture](https://www.datasciencecentral.com/profiles/blogs/number-representation-systems-explained-in-one-picture)
 - Abductive Learning: Towards Bridging Machine Learning and Logical Reasoning: [Slides](http://daiwz.net/org/slides/ABL-meetup.html) | [Video](https://www.youtube.com/watch?v=ETHrFxiFIUM) | [GitHub](https://github.com/AbductiveLearning/ABL-HED)
 
 ## Statistics
 
+- [Statistics Fundamentals](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/fundamentals/statistics-fundamentals/statistics-fundamentals.md)
 - [Statistics for Machine learning (paid book: Packt Publishing)](https://www.packtpub.com/big-data-and-business-intelligence/statistics-machine-learning)
 - [Topic-wise notes: maths & stats](https://www.ctanujit.org/lecture-notes.html)
 - [5 Lesson 5 Measures Of Skewness And Kurtosis](https://sol.du.ac.in/mod/book/view.php?chapterid=1067&id=1317) [deadlink]

diff --git a/guides.md b/guides.md
@@ -6,6 +6,7 @@ This section will be dedicated to guides to learning Data Science, Machine Learn
   - [Existing guides](#existing-guides)
     - [Learning to learn](#learning-to-learn)
     - [Just beginning](#just-beginning)
+    - [Fundamentals](#fundamentals)  
     - [Machine Learning](#machine-learning)
     - [New To Data Science](#new-to-data-science)
     - [Data Science skills](#data-science-skills)
@@ -32,11 +33,19 @@ This section will be dedicated to guides to learning Data Science, Machine Learn
 #### Just beginning
   - [Demystification of the key concepts of Artificial Intelligence and Machine Learning](https://github.com/virgili0/Virgilio/blob/master/Topics/Demystification.md)
 
+#### Fundamentals
+  - [Math Fundamentals](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/fundamentals/math-fundamentals/math-fundamentals.md)
+  - [Statistics Fundamentals](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/fundamentals/statistics-fundamentals/statistics-fundamentals.md)
+  - [Python Fundamentals](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/fundamentals/python-fundamentals/python-fundamentals.md)
+  - [Jupyter Notebook](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/fundamentals/jupyter-notebook/jupyter-notebook.md)
+  - [The Data Science Process](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/fundamentals/the-data-science-process/the-data-science-process.md)
+
 #### Machine Learning
   - [What do I need for ML?](https://github.com/virgili0/Virgilio/blob/master/Topics/prerequisites.md)
   - [Do you really need ML?](https://github.com/virgili0/Virgilio/blob/master/Topics/do_you_need_ml.md)
   - [ML use cases](https://github.com/virgili0/Virgilio/blob/master/Topics/use-cases.md)
   - [Introduction to ML](https://github.com/virgili0/Virgilio/blob/master/Topics/MLSystems.md)
+  - [Machine Learning Theory](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/select-and-train-machine-learning-models/machine-learning-theory/machine-learning-theory.md)
   - [Introduction to Artificial Neural Networks](https://github.com/virgili0/Virgilio/blob/master/Topics/ANN.md)
   - ML Study paths
     - [Machine Learning Study Path](https://github.com/virgili0/Virgilio/blob/master/LearningPaths/Machine%20Learning%20Engineer%20Career%20Path)
@@ -50,12 +59,18 @@ This section will be dedicated to guides to learning Data Science, Machine Learn
 
 #### Data Science skills
   - [The Data Science Process](https://github.com/virgili0/Virgilio/blob/master/Topics/ds_process.md)
-  - [Frame The Problem](https://github.com/virgili0/Virgilio/blob/master/Topics/frame-the-problem.md)
-  - [Usage and Integration](https://github.com/virgili0/Virgilio/blob/master/Topics/usage-and-integration.md)
-  - [Data Preprocessing](https://github.com/virgili0/Virgilio/blob/master/Specializations/HardSkills/DataPreprocessing.md)
-  - [Data Visualization](https://github.com/virgili0/Virgilio/blob/master/Specializations/HardSkills/DataVisualization.md)
+    - [Frame The Problem](https://github.com/virgili0/Virgilio/blob/master/Topics/frame-the-problem.md)
+    - [Usage and Integration](https://github.com/virgili0/Virgilio/blob/master/Topics/usage-and-integration.md)
+    - [Starting a Data Project](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/define-the-scope-and-ask-questions/starting-a-data-project/starting-a-data-project.md)
+    - [WorkSpace Setup and Cloud Computing](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/define-the-scope-and-ask-questions/workspace-setup-and-cloud-computing/workspace-setup-and-cloud-computing.md)
+    - Collect and Prepare Data
+      [Data Preparation](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/collect-and-prepare-data/data-preparation/data-preparation.md)
+      [Data Visualization](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/collect-and-prepare-data/data-visualization/data-visualization.md)
+    - [Data Preprocessing](https://github.com/virgili0/Virgilio/blob/master/Specializations/HardSkills/DataPreprocessing.md)
+    - [Data Visualization](https://github.com/virgili0/Virgilio/blob/master/Specializations/HardSkills/DataVisualization.md)
 
 #### Deep Learning
+  - [Deep Learning Theory](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/select-and-train-machine-learning-models/deep-learning-theory/deep-learning-theory.md)
   - [Deep Learning in Cloud](https://github.com/virgili0/Virgilio/blob/master/Topics/Deep%20learning%20in%20cloud)
   - [Object Tracking based on Deep Learning](https://github.com/virgili0/Virgilio/blob/master/Topics/Computer%20Vision/Object_Tracking_based_on_Deep_Learning.ipynb)
   - [Object Instance Segmentation using TensorFlow Framework and Cloud GPU Technology](https://github.com/virgili0/Virgilio/blob/master/Topics/Computer%20Vision/Object_Instance_Segmentation_using_TensorFlow_Framework_and_Cloud_GPU_Technology.ipynb)

diff --git a/notebooks/README.md b/notebooks/README.md
@@ -2,6 +2,7 @@
 
 ## Notebook Applications and Extensions
 
+- [Jupyter Notebook](https://github.com/virgili0/Virgilio/blob/master/serving/purgatorio/fundamentals/jupyter-notebook/jupyter-notebook.md)
 - Apache Zeppelin notes
   - See [example](../examples/apache-zeppelin/README.md) in the `examples/apache-zeppelin` folder
 - JuPyteR notebooks