From 53f7e3d9530817e4c98cc64da7cfbe9ca3f80359 Mon Sep 17 00:00:00 2001
From: DaedalusDreamJournal
 <71222665+DaedalusDreamJournal@users.noreply.github.com>
Date: Sat, 26 Sep 2020 21:25:26 +0200
Subject: [PATCH] Update Roadmap.md

I added links in section 4.0 and 5.0 ... but I do have some issues with the html 'markers' ... I think I forgot something to 'hide' the link into a zone 'link to the course', like was done here before (for clarity purposes).

And I messed up something somewhere as the single link that I have put on Deep Learning ended up at the end of the roadmap for some reason. :O I assume I must have forgotten a marker to indicate the end of a section or something, which might be why it is messed up right now.

Can I ask someone who's a bit better to correct and, after having done so, to tell me and everyone else where I messed up? It would be useful and will prevent more avoidable corrections in the future and, in general, would make life easier for everyone here I believe :)
---
 Roadmap.md | 46 ++++++++++++++++++++++++++++++++++++++++++++--
 1 file changed, 44 insertions(+), 2 deletions(-)

diff --git a/Roadmap.md b/Roadmap.md
index b431474..7fa58fa 100644
--- a/Roadmap.md
+++ b/Roadmap.md
@@ -262,6 +262,36 @@ It is not necessary to complete all the courses mentioned below. If you feel tha
 <br><br>
 
 ## 4.0 Machine Learning (To Be Completed)
+<table>
+  <tr>
+    <td>Index</td>
+    <td>Course Name</td>
+    <td>Link</td>
+    <td>Description</td>
+  </tr>
+
+  <tr>
+    <td>2.</td>
+    <td>9 Key Machine Learning Algorithms Explained in Plain English>Link to the Course</a></td>
+    <td>https://www.freecodecamp.org/news/a-no-code-intro-to-the-9-most-important-machine-learning-algorithms-today/</td>
+    <td>A very useful intro to 9 of the most used machine learning algorithms used. Even better, it is light on pure maths, and more heavy on the explaining concepts side ... and using normal and plain english to boot! IMPORTANT! -> Be sure to check the rest of the site as you'll probably find a ton of other useful stuff there!</td>
+ </tr>
+
+  <tr>
+    <td>2.</td>
+    <td>Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems>Link to the Course</a></td>
+    <td>https://www.amazon.com/Hands-Machine-Learning-Scikit-Learn-TensorFlow/dp/1492032646/ref=as_li_ss_tl?dchild=1&keywords=scikit+learn&qid=1598661723&sr=8-5&linkCode=sl1&tag=kenjee-20&linkId=1a01eae222ae8d24bc9e3d57b223f94a&language=en_US</td>
+    <td>A book with practical ML examples focusing on both the scikit-learn and tensorflow libraries. A must that has been recommended by many ML experts!</td>
+ </tr>
+    <td>3.</td>
+    <td>Approaching (Almost) Any Machine Learning Problem (Book)</td>
+    <td><a href="https://www.amazon.com/Approaching-Almost-Machine-Learning-Problem-ebook/dp/B089P13QHT/ref=as_li_ss_tl?dchild=1&keywords=abhishek+thakur&qid=1598661786&sr=8-1&linkCode=sl1&tag=kenjee-20&linkId=43f219fc9875e634f0a5536acd4fa781&language=en_US">Link to the Course</a></td>
+    <td>If you have a bit of theoretical knowledege, it is a useful book to find guidance to find solutions where machine learning is useful!</td>
+  </tr>
+</table>
+<br><br>
+
+
 
 <br>
 
@@ -278,8 +308,20 @@ It is not necessary to complete all the courses mentioned below. If you feel tha
 <br><br>
 
 ## 5.0 Deep Learning (To Be Completed)
-
-<br>
+<table>
+  <tr>
+    <td>Index</td>
+    <td>Course Name</td>
+    <td>Link</td>
+    <td>Description</td>
+  </tr>
+ <tr>
+    <td>1.</td>
+    <td>The fastai book -(Github repo) >Link to the Course</a></td>
+    <td>https://github.com/fastai/fastbook/blob/master/README.md</td>
+    <td>This github repo contains notebooks that can be used as an introduction to deep learning, fasti, pytorch and the like. Since it comes with notebook, you can learn and practice at the same time!</td>
+ </tr>
+ <br><br>
 
 ### Artificial Neural Networks