Full codes linked

Author: enesdemirag

exercises/approximating-pi.md

@@ -184,7 +184,7 @@ def distance(x, y):
         print(pi)
 ```
 
-Simulation:
+Simulation: code is [here](materials/approximating-pi/simulation.py).
 <p align="center">
 <img src="images/monte-carlo.gif">
 </p>

exercises/fuzzy-search.md

@@ -9,13 +9,14 @@ To find the similarity, we need to give ranks to every file and return the one w
 ### Practical - Fuzzy Search
 
 Write a function that gets an input, and returns the most similar results in a file.
+Example movie list is [here](materials/fuzzy-search/movielist.txt).
 
 ```python
 def distance(string, pattern): # Levenshtein Distance
     string = " " + string.lower() # Make lowercase
     pattern = " " + pattern.lower() # Make lowercase
 
-    matrix = {}  Empty matrix
+    matrix = {} # Empty matrix
 
     for i in range(len(string)):
         matrix[i, 0] = i # Fill first row from 0 to length of the string
@@ -33,7 +34,7 @@ def distance(string, pattern): # Levenshtein Distance
     return matrix[len(string) - 1, len(pattern) - 1] # return the value in last element
 
 
-movies = open("movies.txt").read().split("\n") # Get the movie list
+movies = open("movielist.txt").read().split("\n") # Get the movie list
 movies_with_ranks = {} # Create empty dictionary
 
 query = str(input("Enter movie : ")) # input
@@ -52,6 +53,8 @@ for i in range(len(sorted_list)):
         break
 ```
 
+Full code can be accessed from [here](materials/fuzzy-search/search.py).
+
 #### **References:**
 
 _Search Algorithms:_

exercises/image-kernels.md

@@ -78,4 +78,6 @@ def filter(image, kernel):
 
 **Result:**
 
-<p align="center"><img src="images/image-kernels.png"></p>
+<p align="center"><img src="images/image-kernels.png"></p>
+
+_Full code is [here](materials/image-kernels/demo.py)._

exercises/linear-regression.md

@@ -60,7 +60,7 @@ ax[1].legend(["Least Squares Regression Line"])
 plt.show()
 ```
 
-The result should be like this.
+The result should be like this. Code can be accessed from [here](materials/linear-regression/regression.py).
 
 <p align="center">
   <img src="images/regression-result.png">

exercises/markov-chains.md

@@ -66,3 +66,5 @@ def run(n, initialWordIndex):
 learn(text)
 run(100, 0)
 ```
+
+You can find the working example code from [here](materials/markov-chains/demo.py).

exercises/mass-spring-damper-simulation.md

@@ -77,7 +77,7 @@ def set(arg):
 Visualizer(callback=set, interval=dt * 1000, simulation_time=30, initial=(position, 0, velocity, 0, acceleration, 0))
 ```
 
-The result should be like this.
+The result should be like this. You can find the full code from [here](materials/mass-spring-damper-simulation/demo.py).
 
 <p align="center">
   <img src="images/msd-simulation.gif">

exercises/perlin-noise.md

@@ -72,7 +72,7 @@ mlab.surf(z) # Surface Plot
 mlab.show()
 ```
 
-The result should be like this.
+The result should be like this. You can find the full code from [here](materials/perlin-noise/opensimplex-demo.py).
 
 <p align="center">
   <img src="images/3d-simplex.png">