Fixing and adding links to the README and README-details section, and…

… pages in the details folder
vishweshs4 · Nov 4, 2019 · a8f21a4 · a8f21a4
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diff --git a/README-details.md b/README-details.md
@@ -80,13 +80,14 @@ See [Mathematics, Statistics, Probability & Probabilistic programming](./details
     - [Feature engineering](./data/README.md#feature-engineering)
     - [Post model-creation analysis, ML interpretation/explainability](./data/README.md#post-model-creation-analysis-ml-interpretationexplainability)
     - [Programs and Tools](./data/programs-and-tools.md#programs-and-tools)
-    - [and other related topics: Stats, Visualisations, Cheatsheets, etc...](data/README.md#data)
+    - **[and other related topics: Stats, Visualisations, Cheatsheets, etc...](data/README.md#data)**
   - [Data Science at the Command Line](https://www.datascienceatthecommandline.com) | [References](https://www.datascienceatthecommandline.com/references.html) | [on GitHub](https://github.com/jeroenjanssens/data-science-at-the-command-line) | [Docker image with 80 CLI tools](https://hub.docker.com/r/datascienceworkshops/data-science-at-the-command-line) | [Appendix: List of Command-Line Tools](http://www.ruxizhang.com/uploads/4/4/0/2/44023465/janssens2014.pdf#%5B%7B%22num%22%3A1880%2C%22gen%22%3A0%7D%2C%7B%22name%22%3A%22XYZ%22%7D%2Cnull%2C589.5%2Cnull%5D) | [Linux Command-Line resource by Chris Albon](https://chrisalbon.com/#linux)
   - [Awesome Datascience](https://github.com/bulutyazilim/awesome-datascience)
   - [Awesome Learn Datascience](https://github.com/siboehm/awesome-learn-datascience)
   - [Data Science for Dummies](http://file.allitebooks.com/20170304/Data%20Science%20For%20Dummies,%202nd%20Edition.pdf)
   - [Data Science resources (scattered across the page)](https://github.com/ayonroy2000/100DaysOfML_TelegramGroup/blob/master/Resources.md)
   - [Learn Data Science by bitgrit](https://github.com/bitgrit-official/learndatascience)
+  - **[and other related topics: Stats, Visualisations, Cheatsheets, etc...](data/README.md#data)**
 
 ### Graphs
   - [A number of interesting links on Graph Networks by Yaz](https://github.com/yazdotai/graph-networks)

diff --git a/README.md b/README.md
@@ -58,7 +58,7 @@ Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn
   - [JavaScript](README-details.md#javascript)
   - [Swift for TensorFlow](https://www.tensorflow.org/swift/) - next generation platform for deep learning and differentiable programming
   - **[Things to know...](./things-to-know.md)**
-  - [Mathematica](README-details.md#mathematica)
+  - [Mathematica](./details/mathematica-wolfram-Language.md#mathematica--wolfram-language)
   - [Mathematics, Statistics, Probability & Probabilistic programming](./details/maths-stats-probability.md#mathematics-statistics-probability--probabilistic-programming)
   - [Data](README-details.md#data)
   - [Visualisation](./details/visualisation.md#visualisation)
@@ -69,9 +69,9 @@ Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn
   - [Notebooks](./notebooks/README.md#notebooks)
   - [Presentations](README-details.md#presentations)
   - [Models](README-details.md#models)
-  - [Articles, papers, code, data, courses](./README-details.md#articles-papers-code-data-courses-presentations)
+  - [Articles, papers, code, data, courses](./details/articles-papers-code-data-courses.md#articles-papers-code-data-courses)
   - [Cheatsheets](./details/cheatsheets.md#cheatsheets)
-  - [Misc](README-details.md#misc-1)
+  - [Misc](./details/misc.md#misc)
 - [Contributing](#contributing)
 
 # Contributing

diff --git a/details/java-jvm.md b/details/java-jvm.md
@@ -75,7 +75,7 @@ Dataiku DSS: [![Dataiku DSS](https://img.shields.io/docker/pulls/neomatrix369/da
 
 ## Natural Language Processing (NLP)
 
-  - See [Natural Language Processing (NLP)](natural-language-processing/README.md#Java-jvm)
+  - See [Java/JVM](../natural-language-processing/java-jvm.md#javajvm) in [Natural Language Processing (NLP)](../natural-language-processing#natural-language-processing-nlp)
 
 ## Neural Networks
 
@@ -117,9 +117,9 @@ Dataiku DSS: [![Dataiku DSS](https://img.shields.io/docker/pulls/neomatrix369/da
 - [A visual introduction to machine learning](http://www.r2d3.us/visual-intro-to-machine-learning-part-1/)
 - 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)
 - [Overview of AI Libraries in Java](https://www.baeldung.com/java-ai)
-- See [ML on Code/Programm/Source Code](./ML-on-code-programming-source-code.md)
-- See [Cloud/DevOps/Infra > Performance](./cloud-devops-infra/README.md#performance) - to find various ML performance benchmarking suites
-- Also see [Post model-creation analysis, ML interpretation/explainability](./data/README.md#post-model-creation-analysis-ml-interpretationexplainability)
+- See [ML on Code/Programm/Source Code](../ML-on-code-programming-source-code.md)
+- See [Cloud/DevOps/Infra > Performance](../cloud-devops-infra/README.md#performance) - to find various ML performance benchmarking suites
+- Also see [Post model-creation analysis, ML interpretation/explainability](../data/README.md#post-model-creation-analysis-ml-interpretationexplainability)
 
 ### Deep learning
 
@@ -184,7 +184,7 @@ Dataiku DSS: [![Dataiku DSS](https://img.shields.io/docker/pulls/neomatrix369/da
 
 ## Visualisation
 
-See [Visualisation](./details/visualisation.md#visualisation)
+See [Visualisation](./visualisation.md#visualisation)
 
 # Contributing
 

diff --git a/details/julia-python-and-r.md b/details/julia-python-and-r.md
@@ -50,7 +50,7 @@
 
   ## Natural Language Processing (NLP)
 
-  - See [Natural Language Processing (NLP)](natural-language-processing/README.md#natural-language-processing-nlp)
+  - See [Natural Language Processing (NLP)](../natural-language-processing/README.md#natural-language-processing-nlp)
 
   ## Computer Vision
 
@@ -133,9 +133,9 @@
   - [A number of useful ML related repositories](https://github.com/chrisalbon?tab=repositories) by [Chris Albon](https://github.com/chrisalbon)
   - [ML topics expanded by Chris Albon](https://chrisalbon.com/#machine_learning) - topics covered: Vectors, Matrices, And Arrays • ML Basics • Preprocessing Structured Data • Preprocessing Images • Preprocessing Text • Preprocessing Dates And Times • Feature Engineering • Feature Selection • Model Evaluation • Model Selection • Linear Regression • Logistic Regression • Trees And Forests • Nearest Neighbors • Support Vector Machines • Naive Bayes • Clustering
   - [Claoudml](https://www.claoudml.com/) - Free Data Science & Machine Learning Resources
-  - See [ML on Code/Programm/Source Code](./ML-on-code-programming-source-code.md)
-  - See [Cloud/DevOps/Infra > Performance](./cloud-devops-infra/README.md#performance) - to find various ML performance benchmarking suites
-  - Also see [Post model-creation analysis, ML interpretation/explainability](./data/README.md#post-model-creation-analysis-ml-interpretationexplainability)
+  - See [ML on Code/Programm/Source Code](../ML-on-code-programming-source-code.md)
+  - See [Cloud/DevOps/Infra > Performance](../cloud-devops-infra/README.md#performance) - to find various ML performance benchmarking suites
+  - Also see [Post model-creation analysis, ML interpretation/explainability](../data/README.md#post-model-creation-analysis-ml-interpretationexplainability)
 
   ### Deep Learning
 
@@ -150,7 +150,7 @@
    - [Sebastian Ruder, Research scientist, DeepMind - Machine Learning, Deep Learning, & NLP](http://ruder.io/)
    - [Learning Deep Learning with Keras](http://p.migdal.pl/2017/04/30/teaching-deep-learning.html)
    - [Starting deep learning hands-on: image classification on CIFAR-10](https://blog.deepsense.ai/deep-learning-hands-on-image-classification/)
-   - [Checkout 'Deep Learning with Tensorflow 2.0 (MNIST)' Notebooks](https://github.com/neomatrix369/awesome-ai-ml-dl/blob/master/README-details.md#notebooks)
+   - [Checkout 'Deep Learning with Tensorflow 2.0 (MNIST)' Notebooks](../notebooks/README.md#notebooks)
    - [Deep learning for 3D printing manufacturing](https://www.youtube.com/watch?v=jAQSM2dhDV4) by [Benjamin Schrauwen](https://www.linkedin.com/in/benjaminschrauwen)
    - [DL topics expanded by Chris Albon](https://chrisalbon.com/#deep_learning) - topics covered: Keras 
 
@@ -179,7 +179,7 @@
 
 ## Visualisation
 
-See [Visualisation](./details/visualisation.md#visualisation)
+See [Visualisation](./visualisation.md#visualisation)
 
 ## More...