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Author: amoshnin

README.md

@@ -21,17 +21,17 @@ My assignments for CS50's Introduction to Artificial Intelligence with Python.
             <td>Discover it how many "degress of separation" apart two actors are.</td>
             <td>Breadth First Search</td>
             <td>
-                <a href="https://www.youtube.com/watch?v=bwd0eSYMlmM&t=28s">Video link</a>
-                <a href="https://cs50.harvard.edu/ai/2020/projects/0/degrees/">Theory link</a>
+                <a href="https://www.youtube.com/watch?v=bwd0eSYMlmM&t=28s">Video</a>
+                <a href="https://cs50.harvard.edu/ai/2020/projects/0/degrees/">Theory</a>
             </td>
         </tr>
         <tr>
             <td><a href="./0-search/0b-tictactoe">Tic tac toe</a></td>
             <td>Play tic-tac-toe against an AI that plays optimally.</td>
             <td>Minimax Algorithm</td>
             <td>
-                <a href="https://www.youtube.com/watch?v=ukjCBsOTEFI">Video link</a>
-                <a href="https://cs50.harvard.edu/ai/2020/projects/0/tictactoe/">Theory link</a>
+                <a href="https://www.youtube.com/watch?v=ukjCBsOTEFI">Video</a>
+                <a href="https://cs50.harvard.edu/ai/2020/projects/0/tictactoe/">Theory</a>
             </td>
         </tr>
         <tr>
@@ -40,73 +40,73 @@ My assignments for CS50's Introduction to Artificial Intelligence with Python.
             <td>A program to solve logic puzzles.</td>
             <td>Propositional Logic</td>
             <td>
-                <a href="https://www.youtube.com/watch?v=h_FmpQOj81M">Video link</a>
-                <a href="https://cs50.harvard.edu/ai/2020/projects/1/knights/">Theory link</a>
+                <a href="https://www.youtube.com/watch?v=h_FmpQOj81M">Video</a>
+                <a href="https://cs50.harvard.edu/ai/2020/projects/1/knights/">Theory</a>
             </td>
         </tr>
         <tr>
             <td><a href="./1-knowledge/1b-minesweeper">Minesweeper</a></td>
             <td>Play minesweeper or let the AI play for you.</td>
             <td>Propositional Logic</td>
             <td>
-                <a href="https://www.youtube.com/watch?v=Uz8VEFvfnOU">Video link</a>
-                <a href="https://cs50.harvard.edu/ai/2020/projects/1/minesweeper/">Theory link</a>
+                <a href="https://www.youtube.com/watch?v=Uz8VEFvfnOU">Video</a>
+                <a href="https://cs50.harvard.edu/ai/2020/projects/1/minesweeper/">Theory</a>
             </td>
         </tr>
         <tr>
             <td rowspan=2>Uncertainty</td>
             <td><a href="./2-uncertainty/2a-pagerank">Pagerank</a></td>
-            <td>PageRank works by counting the number and quality of links to a page to determine a rough estimate of how important the website is</td>
+            <td>PageRank works by counting the number and quality ofs to a page to determine a rough estimate of how important the website is</td>
             <td>PageRank algorithm created by Google's CoFounders</td>
             <td>
-                <a href="https://cs50.harvard.edu/ai/2020/projects/2/pagerank/">Theory link</a>
+                <a href="https://cs50.harvard.edu/ai/2020/projects/2/pagerank/">Theory</a>
             </td>
         </tr>
         <tr>
             <td><a href="./2-uncertainty/2b-heredity">Heredity</a></td>
             <td>Bayesian Network of genes is used by AI to infer the probability distribution for each person’s genes, as well as the probability distribution for whether any person will exhibit the trait in question</td>
             <td>Probability theory: Probability distribution and Joint Probability</td>
-            <td><a href="https://cs50.harvard.edu/ai/2020/projects/2/heredity/">Theory link</a></td>
+            <td><a href="https://cs50.harvard.edu/ai/2020/projects/2/heredity/">Theory</a></td>
         </tr>
         <tr>
             <td rowspan=1>Optimization</td>
             <td><a href="./3-optimization/3a-crossword">Crossword</a></td>
             <td>Generating a crossword puzzle</td>
             <td>Modelled as constraint satisfaction problem</td>
-            <td><a href="https://cs50.harvard.edu/ai/2020/projects/3/crossword/">Theory link</a></td>
+            <td><a href="https://cs50.harvard.edu/ai/2020/projects/3/crossword/">Theory</a></td>
         </tr>
         <tr>
             <td rowspan=2>Learning</td>
             <td><a href="./4-learning/4a-shopping">Shopping</a></td>
             <td>Determining the likelihood of a user making a purchase on a website</td>
             <td>Nearest-neighbor classifier</td>
-            <td><a href="https://cs50.harvard.edu/ai/2020/projects/4/shopping/">Theory link</a></td>
+            <td><a href="https://cs50.harvard.edu/ai/2020/projects/4/shopping/">Theory</a></td>
         </tr>
         <tr>
             <td><a href="./4-learning/4b-nim">Nim</a></td>
             <td>Learning best strategy for playing Nim with more than one pile</td>
             <td>Reinforcment Learning AI</td>
-            <td><a href="https://cs50.harvard.edu/ai/2020/projects/4/nim/">Theory link</a></td>
+            <td><a href="https://cs50.harvard.edu/ai/2020/projects/4/nim/">Theory</a></td>
         </tr>
         <tr>
             <td rowspan=1>Neural Networks</td>
             <td><a href="./5-neural_networks/5a-traffic">Traffic</a></td>
             <td>Neural networks for road signs classification (useful for self-driving cars) using GTSRB</td>
             <td>Computer Vision with Neural Networks (Tensorflow)</td>
-            <td><a href="https://cs50.harvard.edu/ai/2020/projects/5/traffic/">Theory link</a></td>
+            <td><a href="https://cs50.harvard.edu/ai/2020/projects/5/traffic/">Theory</a></td>
         </tr>
         <tr>
             <td rowspan=2>Language</td>
             <td><a href="./6-language/6a-parser">Parser</a></td>
             <td>Determining the structure of a sentence by parsing for information/meaning extraction</td>
             <td>Context-free grammar formalism</td>
-            <td><a href="https://cs50.harvard.edu/ai/2020/projects/6/parser/">Theory link</a></td>
+            <td><a href="https://cs50.harvard.edu/ai/2020/projects/6/parser/">Theory</a></td>
         </tr>
         <tr>
             <td><a href="./6-language/6b-questions">Questions</a></td>
             <td>Perform Question Answering (QA) with document retrieval and passage retrieval tasks. Document retrieval will first identify which document(s) are most relevant to the query. Once the top documents are found, the top document(s) will be subdivided into passages so that the most relevant passage to the question can be determined.</td>
             <td>Most relevant documents/passages are determined by tf-idf to rank documents and query term density measure metric for scoring passages</td>
-            <td><a href="https://cs50.harvard.edu/ai/2020/projects/6/questions/">Theory link</a></td>
+            <td><a href="https://cs50.harvard.edu/ai/2020/projects/6/questions/">Theory</a></td>
         </tr>
     </tbody>