Artificial Intelligence

1
2class sentencebert_ai():
3    def __init__(self) -> None:
4        super().__init__()
5
6 def ask_query(self,query, topN):
7        startt = time.time()
8
9        ask_result = []
10        score = []
11        result_value = []  
12        embedder = torch.load(model_path)
13        corpus_embeddings = embedder.encode(corpus, convert_to_tensor=True)
14        query_embedding = embedder.encode(query, convert_to_tensor=True)
15        cos_scores = util.pytorch_cos_sim(query_embedding, corpus_embeddings)[0] #torch.Size([121])121개의 말뭉치에 대한 코사인 유사도 값이다.
16        cos_scores = cos_scores.cpu()
17
18        top_results = np.argpartition(-cos_scores, range(topN))[0:topN]
19
20        for idx in top_results[0:topN]:        
21            ask_result.append(corpusid[idx].item())
22            #.item()으로 접근하는 이유는 tensor(5)에서 해당 숫자에 접근하기 위한 방식이다.
23            score.append(round(cos_scores[idx].item(),3))
24
25        #서버에 json array 형태로 내보내기 위한 작업
26        for i,e in zip(ask_result,score):
27            result_value.append({"pred_id":i,"pred_weight":e})
28        endd = time.time()
29        print('시간체크',endd-startt)
30        return result_value
31        # return ','.join(str(e) for e in ask_result),','.join(str(e) for e in score)
32
33
34
35class Item_inference(BaseModel):
36    text : str
37    topN : Optional[int] = 1
38
39@app.post("/retrieval", tags=["knowledge recommendation"])
40async def Knowledge_recommendation(item: Item_inference):
41  
42    # db.append(item.dict())
43    item.dict()
44    results = _ai.ask_query(item.text, item.topN)
45
46    return results
47
48
49if __name__ == "__main__":
50    parser = argparse.ArgumentParser()
51    parser.add_argument("--port", default='9003', type=int)
52    # parser.add_argument("--mode", default='cpu', type=str, help='cpu for CPU mode, gpu for GPU mode')
53    args = parser.parse_args()
54
55    _ai = sentencebert_ai()
56    uvicorn.run(app, host="0.0.0.0", port=args.port,workers=4)
57

1
2class sentencebert_ai():
3    def __init__(self) -> None:
4        super().__init__()
5
6 def ask_query(self,query, topN):
7        startt = time.time()
8
9        ask_result = []
10        score = []
11        result_value = []  
12        embedder = torch.load(model_path)
13        corpus_embeddings = embedder.encode(corpus, convert_to_tensor=True)
14        query_embedding = embedder.encode(query, convert_to_tensor=True)
15        cos_scores = util.pytorch_cos_sim(query_embedding, corpus_embeddings)[0] #torch.Size([121])121개의 말뭉치에 대한 코사인 유사도 값이다.
16        cos_scores = cos_scores.cpu()
17
18        top_results = np.argpartition(-cos_scores, range(topN))[0:topN]
19
20        for idx in top_results[0:topN]:        
21            ask_result.append(corpusid[idx].item())
22            #.item()으로 접근하는 이유는 tensor(5)에서 해당 숫자에 접근하기 위한 방식이다.
23            score.append(round(cos_scores[idx].item(),3))
24
25        #서버에 json array 형태로 내보내기 위한 작업
26        for i,e in zip(ask_result,score):
27            result_value.append({"pred_id":i,"pred_weight":e})
28        endd = time.time()
29        print('시간체크',endd-startt)
30        return result_value
31        # return ','.join(str(e) for e in ask_result),','.join(str(e) for e in score)
32
33
34
35class Item_inference(BaseModel):
36    text : str
37    topN : Optional[int] = 1
38
39@app.post("/retrieval", tags=["knowledge recommendation"])
40async def Knowledge_recommendation(item: Item_inference):
41  
42    # db.append(item.dict())
43    item.dict()
44    results = _ai.ask_query(item.text, item.topN)
45
46    return results
47
48
49if __name__ == "__main__":
50    parser = argparse.ArgumentParser()
51    parser.add_argument("--port", default='9003', type=int)
52    # parser.add_argument("--mode", default='cpu', type=str, help='cpu for CPU mode, gpu for GPU mode')
53    args = parser.parse_args()
54
55    _ai = sentencebert_ai()
56    uvicorn.run(app, host="0.0.0.0", port=args.port,workers=4)
57@app.post("/aaa") def your_endpoint(request: Request, item:Item_inference): start = time.time() model = request.app.state.model item.dict() #커널 실행시 필요 _ai = sentencebert_ai() results = _ai.ask_query(item.text, item.topN,model) end = time.time() print(end-start) return results ``` 
58

1class Question:
2    
3    def __init__(self,text,choices,answer):
4        self.text = text
5        self.choices = choices
6        self.answer = answer
7        
8    def checkAnswer(self, answer):
9        return self.answer == answer
10 class Quiz:
11    
12    def __init__(self, questions):
13        self.questions = questions
14        self.score = 0
15        self.questionsIndex = 0
16        
17    def getQuestion(self):
18        return self.questions[self.questionsIndex]
19    
20    def displayQuestion(self):
21        question = self.getQuestion()
22        print(f"Question: {self.questionsIndex +1}: {question.text}")   
23        for q in question.choices:
24            print("-"+ q)
25        answer = input("Your Answer:  ")
26        self.guess(answer)
27        self.loadQuestion()
28        
29    def guess(self, answer):
30        question = self.getQuestion()
31        if question.checkAnswer(answer):
32            self.score += 1
33        self.questionsIndex += 1
34        self.displayQuestion()
35        
36    def loadQuestion(self):
37        if len(self.questions) == self.questionsIndex:
38            self.showScore()
39        else:
40            self.displayProgress()
41            self.displayQuestion()
42            
43    def showScore(self):
44        print("Score: ", self.score)
45        
46    def displayProgress(self):
47        totalQuestion = len(self.questions)
48        questionNumber = self.questionsIndex + 1
49        if questionNumber > totalQuestion:
50            print("Quiz Finished")
51        else:
52            print(f"*************************Question {questionNumber} of {totalQuestion}***********************************")
53           
54
55q1 = Question("Which programming language is the most profitable?["C#","Python","Java","HTML"],"Python")
56q2 = Question("Which is the easiest programming language?", ["C#","Python","Java","HTML"],"Python")
57q3 = Question("What is the most popular programming language?", ["C#","Python","Java","HTML"],"Python")
58questions = [q1,q2,q3]
59quiz = Quiz(questions)
60quiz.loadQuestion()
61

1class Question:
2    
3    def __init__(self,text,choices,answer):
4        self.text = text
5        self.choices = choices
6        self.answer = answer
7        
8    def checkAnswer(self, answer):
9        return self.answer == answer
10 class Quiz:
11    
12    def __init__(self, questions):
13        self.questions = questions
14        self.score = 0
15        self.questionsIndex = 0
16        
17    def getQuestion(self):
18        return self.questions[self.questionsIndex]
19    
20    def displayQuestion(self):
21        question = self.getQuestion()
22        print(f"Question: {self.questionsIndex +1}: {question.text}")   
23        for q in question.choices:
24            print("-"+ q)
25        answer = input("Your Answer:  ")
26        self.guess(answer)
27        self.loadQuestion()
28        
29    def guess(self, answer):
30        question = self.getQuestion()
31        if question.checkAnswer(answer):
32            self.score += 1
33        self.questionsIndex += 1
34        self.displayQuestion()
35        
36    def loadQuestion(self):
37        if len(self.questions) == self.questionsIndex:
38            self.showScore()
39        else:
40            self.displayProgress()
41            self.displayQuestion()
42            
43    def showScore(self):
44        print("Score: ", self.score)
45        
46    def displayProgress(self):
47        totalQuestion = len(self.questions)
48        questionNumber = self.questionsIndex + 1
49        if questionNumber > totalQuestion:
50            print("Quiz Finished")
51        else:
52            print(f"*************************Question {questionNumber} of {totalQuestion}***********************************")
53           
54
55q1 = Question("Which programming language is the most profitable?["C#","Python","Java","HTML"],"Python")
56q2 = Question("Which is the easiest programming language?", ["C#","Python","Java","HTML"],"Python")
57q3 = Question("What is the most popular programming language?", ["C#","Python","Java","HTML"],"Python")
58questions = [q1,q2,q3]
59quiz = Quiz(questions)
60quiz.loadQuestion()
61runfile('C:/Users/Onur/Desktop/Artificial Intelligence A-Z/sorularclass.py', wdir='C:/Users/Onur/Desktop/Artificial Intelligence A-Z')
62*************************Question 1 of 3***********************************
63Question: 1: Which programming language is the most profitable?
64-C#
65-Python
66-Java
67-HTML
68 Your Answer:  a
69Question: 2: Which is the easiest programming language?
70-C#
71-Python
72-Java
73-HTML
74Your Answer:  a
75Question: 3: What is the most popular programming language?
76-C#
77-Python
78-Java
79-HTML
80Your Answer:  a
81Traceback (most recent call last):
82File "C:\Users\Onur\Desktop\Artificial Intelligence A-Z\sorularclass.py", line 63, in <module>
83    quiz.loadQuestion()
84File "C:\Users\Onur\Desktop\Artificial Intelligence A-Z\sorularclass.py", line 44, in loadQuestion
85    self.displayQuestion()
86File "C:\Users\Onur\Desktop\Artificial Intelligence A-Z\sorularclass.py", line 29, in displayQuestion
87    self.guess(answer)
88File "C:\Users\Onur\Desktop\Artificial Intelligence A-Z\sorularclass.py", line 37, in guess
89    self.displayQuestion()
90File "C:\Users\Onur\Desktop\Artificial Intelligence A-Z\sorularclass.py", line 29, in displayQuestion
91    self.guess(answer)
92File "C:\Users\Onur\Desktop\Artificial Intelligence A-Z\sorularclass.py", line 37, in guess
93    self.displayQuestion()
94File "C:\Users\Onur\Desktop\Artificial Intelligence A-Z\sorularclass.py", line 29, in displayQuestion
95    self.guess(answer)
96File "C:\Users\Onur\Desktop\Artificial Intelligence A-Z\sorularclass.py", line 37, in guess
97    self.displayQuestion()
98File "C:\Users\Onur\Desktop\Artificial Intelligence A-Z\sorularclass.py", line 24, in displayQuestion
99    question = self.getQuestion()
100File "C:\Users\Onur\Desktop\Artificial Intelligence A-Z\sorularclass.py", line 21, in getQuestion
101    return self.questions[self.questionsIndex]
102
103IndexError: list index out of range
104

1X = df.copy()
2y = X.pop('shares') 
3
4# scaling the dataset so all data in the same range
5scaler = preprocessing.MinMaxScaler()
6X = scaler.fit_transform(X)
7
8discretizer = preprocessing.KBinsDiscretizer(n_bins=5,  encode='ordinal', strategy='uniform')
9y_discretized = discretizer.fit_transform(y.values.reshape(-1, 1))
10
11# is this correct?
12X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, shuffle=True, stratify=y_discretized) 
13

1* {
2     margin: 0;
3     padding: 0;
4     box-sizing: border-box;
5}
6 body {
7     font-family: 'Source Sans Pro', sans-serif;
8     background-color: black;
9     color: white;
10     line-height: 30px;
11}
12 html {
13     width:100%;
14}
15 img {
16     width: 100%;
17}
18 h1 {
19     font-weight: 700;
20     font-size: 44px;
21     margin-bottom: 40px;
22     line-height: 50px;
23}
24 h3 {
25     width: 100%;
26}
27/* header */
28 header {
29     display: flex;
30     background-color: black;
31     height: 80px;
32     min-width: 1100px;
33     justify-content: right;
34     align-items: center;
35     margin-bottom: 50px;
36     border-bottom: 1px solid white;
37}
38 nav ul li {
39     display: inline-block;
40     list-style-type: none;
41     margin-right: 20px;
42}
43 .nav-links{
44     color: white;
45     font-size: 18px;
46}
47/* Banner */
48 .banner {
49     display: flex;
50     justify-content: space-around;
51     align-items: center;
52     min-height: 500px;
53     width: 100%;
54}
55 .banner-text-container {
56     max-width: 30%;
57     font-size: 22px;
58}
59 span {
60     color: #11cc9e;
61}
62 .consultation-link{
63     color: #11cc9e;
64     text-decoration: none;
65     margin-top: 30px;
66     font-weight: 900;
67     display: block;
68     border: 1px solid white;
69     max-width: 40%;
70     text-align: center;
71     padding: 5px;
72}
73 .consultation-link:hover{
74     background-color: #fff;
75}
76/* About */
77 .about {
78     display: flex;
79     justify-content: space-around;
80     align-items: center;
81     min-height: 600px;
82     min-width: 1100px;
83}
84 .about-text-container {
85     max-width: 40%;
86     font-size: 22px;
87     margin-left: 20px;
88}
89 .about-img{
90     width: 400px;
91     margin-right: 22px;
92}
93 .about-title {
94     margin-bottom: 40px;
95}
96 .about-us-link{
97     color: #11cc9e;
98     text-decoration: none;
99     margin-top: 30px;
100     font-weight: 900;
101     display: block;
102     border: 1px solid white;
103     text-align: center;
104     max-width: 25%;
105     padding: 5px;
106}
107 .about-us-link:hover{
108     background-color: #fff;
109}
110/* Join */
111 .join {
112     min-height: 600px;
113     min-width: 1100px;
114     max-width: 100%;
115}
116 .join-header{
117     width: 100%;
118     text-align: center;
119     margin-top: 150px;
120     font-size: 40px;
121}
122 .container-boxes{
123     position: relative;
124     top: 0;
125     bottom: 0;
126     display: flex;
127     flex-wrap: wrap;
128     justify-content: space-evenly;
129     align-items: center;
130     min-height: 500px;
131     min-width: 1100px;
132}
133 .box {
134     position: relative;
135     overflow: hidden;
136     transition: 0.5s;
137     height: 200px;
138     width: 300px;
139}
140 .box:hover{
141     z-index: 1;
142     transform: scale(1.25);
143     box-shadow: 0 25px 40px rgba(0, 0, 0, .5);
144     cursor: pointer;
145}
146 .box .imgBX{
147     position: absolute;
148     top: 0;
149     left: 0;
150     width: 100%;
151     height: 100%;
152}
153 .box .imgBX img{
154     position: absolute;
155     top: 0;
156     left: 0;
157     width: 100%;
158     height: 100%;
159     object-fit: cover;
160}
161 .box .imgBX:before{
162     content: '';
163     position: absolute;
164     top: 0;
165     left: 0;
166     width: 100%;
167     height: 100%;
168     z-index: 1;
169     background: linear-gradient(180deg,rgba(0,0,0.7),#79dbc3);
170     mix-blend-mode: multiply;
171     opacity: 0;
172     transition: 0.5s;
173}
174 .box:hover .imgBX:before {
175     opacity: 1;
176}
177 .box .imgBX img{
178     position: absolute;
179     top: 0;
180     left: 0;
181     width: 100%;
182     height: 100%;
183     object-fit: cover;
184}
185 .content{
186     display: flex;
187     flex-direction: column;
188     text-align: center;
189     position: absolute;
190     top: 20%;
191     bottom: 40%;
192     width: 100%;
193     height: 100%;
194     z-index: 1;
195     padding: 20px;
196     visibility: hidden;
197}
198 .box:hover .content{
199     visibility: visible;
200}
201/* Quote section */
202 .quote-section {
203     display: flex;
204     justify-content: center;
205     max-width: 100%;
206     min-height: 500px;
207     min-width: 1100px;
208}
209 .quote-container {
210     display: flex;
211     flex-direction: column;
212     flex-wrap: wrap;
213     align-items: center;
214     justify-items: center;
215     max-width: 50%;
216     font-size: 22px;
217     text-align: center;
218}
219 .quote {
220     line-height: 90px;
221     font-size: 150px;
222     font-style: italic;
223     color: #11cc9e;
224     text-indent: -37px;
225     font-weight: 600;
226     width: 37px;
227}
228 .quote-img{
229     width: 90px;
230     margin: 40px auto;
231}
232 .person-name{
233     color: #ccc;
234}
235 .person-role{
236     font-size: 17px;
237     color: #ccc;
238}
239/* Footer */
240 footer {
241     text-align: center;
242     margin-top: 100px;
243     padding-top: 50px;
244     max-width: 100%;
245     min-height: 200px;
246     min-width: 1100px;
247     border-top: 1px solid #fff;
248}

1* {
2     margin: 0;
3     padding: 0;
4     box-sizing: border-box;
5}
6 body {
7     font-family: 'Source Sans Pro', sans-serif;
8     background-color: black;
9     color: white;
10     line-height: 30px;
11}
12 html {
13     width:100%;
14}
15 img {
16     width: 100%;
17}
18 h1 {
19     font-weight: 700;
20     font-size: 44px;
21     margin-bottom: 40px;
22     line-height: 50px;
23}
24 h3 {
25     width: 100%;
26}
27/* header */
28 header {
29     display: flex;
30     background-color: black;
31     height: 80px;
32     min-width: 1100px;
33     justify-content: right;
34     align-items: center;
35     margin-bottom: 50px;
36     border-bottom: 1px solid white;
37}
38 nav ul li {
39     display: inline-block;
40     list-style-type: none;
41     margin-right: 20px;
42}
43 .nav-links{
44     color: white;
45     font-size: 18px;
46}
47/* Banner */
48 .banner {
49     display: flex;
50     justify-content: space-around;
51     align-items: center;
52     min-height: 500px;
53     width: 100%;
54}
55 .banner-text-container {
56     max-width: 30%;
57     font-size: 22px;
58}
59 span {
60     color: #11cc9e;
61}
62 .consultation-link{
63     color: #11cc9e;
64     text-decoration: none;
65     margin-top: 30px;
66     font-weight: 900;
67     display: block;
68     border: 1px solid white;
69     max-width: 40%;
70     text-align: center;
71     padding: 5px;
72}
73 .consultation-link:hover{
74     background-color: #fff;
75}
76/* About */
77 .about {
78     display: flex;
79     justify-content: space-around;
80     align-items: center;
81     min-height: 600px;
82     min-width: 1100px;
83}
84 .about-text-container {
85     max-width: 40%;
86     font-size: 22px;
87     margin-left: 20px;
88}
89 .about-img{
90     width: 400px;
91     margin-right: 22px;
92}
93 .about-title {
94     margin-bottom: 40px;
95}
96 .about-us-link{
97     color: #11cc9e;
98     text-decoration: none;
99     margin-top: 30px;
100     font-weight: 900;
101     display: block;
102     border: 1px solid white;
103     text-align: center;
104     max-width: 25%;
105     padding: 5px;
106}
107 .about-us-link:hover{
108     background-color: #fff;
109}
110/* Join */
111 .join {
112     min-height: 600px;
113     min-width: 1100px;
114     max-width: 100%;
115}
116 .join-header{
117     width: 100%;
118     text-align: center;
119     margin-top: 150px;
120     font-size: 40px;
121}
122 .container-boxes{
123     position: relative;
124     top: 0;
125     bottom: 0;
126     display: flex;
127     flex-wrap: wrap;
128     justify-content: space-evenly;
129     align-items: center;
130     min-height: 500px;
131     min-width: 1100px;
132}
133 .box {
134     position: relative;
135     overflow: hidden;
136     transition: 0.5s;
137     height: 200px;
138     width: 300px;
139}
140 .box:hover{
141     z-index: 1;
142     transform: scale(1.25);
143     box-shadow: 0 25px 40px rgba(0, 0, 0, .5);
144     cursor: pointer;
145}
146 .box .imgBX{
147     position: absolute;
148     top: 0;
149     left: 0;
150     width: 100%;
151     height: 100%;
152}
153 .box .imgBX img{
154     position: absolute;
155     top: 0;
156     left: 0;
157     width: 100%;
158     height: 100%;
159     object-fit: cover;
160}
161 .box .imgBX:before{
162     content: '';
163     position: absolute;
164     top: 0;
165     left: 0;
166     width: 100%;
167     height: 100%;
168     z-index: 1;
169     background: linear-gradient(180deg,rgba(0,0,0.7),#79dbc3);
170     mix-blend-mode: multiply;
171     opacity: 0;
172     transition: 0.5s;
173}
174 .box:hover .imgBX:before {
175     opacity: 1;
176}
177 .box .imgBX img{
178     position: absolute;
179     top: 0;
180     left: 0;
181     width: 100%;
182     height: 100%;
183     object-fit: cover;
184}
185 .content{
186     display: flex;
187     flex-direction: column;
188     text-align: center;
189     position: absolute;
190     top: 20%;
191     bottom: 40%;
192     width: 100%;
193     height: 100%;
194     z-index: 1;
195     padding: 20px;
196     visibility: hidden;
197}
198 .box:hover .content{
199     visibility: visible;
200}
201/* Quote section */
202 .quote-section {
203     display: flex;
204     justify-content: center;
205     max-width: 100%;
206     min-height: 500px;
207     min-width: 1100px;
208}
209 .quote-container {
210     display: flex;
211     flex-direction: column;
212     flex-wrap: wrap;
213     align-items: center;
214     justify-items: center;
215     max-width: 50%;
216     font-size: 22px;
217     text-align: center;
218}
219 .quote {
220     line-height: 90px;
221     font-size: 150px;
222     font-style: italic;
223     color: #11cc9e;
224     text-indent: -37px;
225     font-weight: 600;
226     width: 37px;
227}
228 .quote-img{
229     width: 90px;
230     margin: 40px auto;
231}
232 .person-name{
233     color: #ccc;
234}
235 .person-role{
236     font-size: 17px;
237     color: #ccc;
238}
239/* Footer */
240 footer {
241     text-align: center;
242     margin-top: 100px;
243     padding-top: 50px;
244     max-width: 100%;
245     min-height: 200px;
246     min-width: 1100px;
247     border-top: 1px solid #fff;
248}<!DOCTYPE html>
249<html lang="en">
250   <head>
251      <title>Codes</title>
252      <link rel="preconnect" href="https://fonts.googleapis.com">
253      <ink rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
254      <link href="https://fonts.googleapis.com/css2?family=Source+Sans+Pro:wght@400;600&display=swap" rel="stylesheet">
255      <meta charset="UTF-8">
256      <meta http-equiv="X-UA-Compatible" content="IE=edge">
257      <meta name="viewport" content="width=device-width, initial-scale=1">
258      <link rel="stylesheet" href="./Resources/styles.css">
259   </head>
260   <body>
261      <header>
262         <!-- insert logo -->
263         <nav class="nav-links">
264            <ul>
265               <li>About</li>
266               <li>Peer group</li>
267               <li>Review</li>
268            </ul>
269         </nav>
270      </header>
271      <section class="banner">
272         <div class="banner-text-container">
273            <h1>Build. Grow. <span class="color-Learn">Learn.</span></h1>
274            <p>Unlock your potential with your peers!, using Blockchain, Fintech or the IT outsourcing company Boosty Labs helps you create an innovative end to end product or augment your team with the right experts.</p>
275            <a class="consultation-link" href="#">Free consultation </a>
276         </div>
277         <div class="banner-img">
278            <img src="./Resources/Images/banner.png" alt="">
279         </div>
280      </section>
281      <section class="about">
282         <div class="about-text-container">
283            <h2 class="about-title">Who we are</h2>
284            <p>Here you can find our ,collection of coding, data science and statistics tutorials with examples in R, Python, JavaScript and Python. As you click through, you'll notice that some tutorials have ribbons on their logos - they are part of our free and self-paced online course Data Science for Ecologists and Environmental Scientists! Yellow for the Stats from Scratch stream, blue for Wiz of Data Viz and purple for Mastering Modelling.</p>
285            <a class="about-us-link" href="#">More about us </a>
286         </div>
287         <div class="about-img">
288            <img src="./Resources/Images/whoweare.png" alt="">
289         </div>
290      </section>
291      <section class="join">
292         <h3 class="join-header" >Join a peer group!</h3>
293         <div class="container-boxes">
294            <div class="box">
295               <div class="imgBX"> 
296                  <img src="./Resources/Images/box-1.png" alt="">
297               </div>
298               <div class="content">
299                  <h3>AI</h3>
300                  <P>Discover The Complete Range Of Artificial Intelligence Solutions.</P>
301               </div>
302            </div>
303            <div class="box">
304               <div class="imgBX">
305                  <img src="./Resources/Images/box-2.png" alt="">
306               </div>
307               <div class="content">
308                  <h3 class="frontend-title">Frontend Dev</h3>
309                  <p>Discover The Complete Range Of Frontend Solutions.</p>
310               </div>
311            </div>
312            <div class="box">
313               <div class="imgBX">
314                  <img src="./Resources/Images/box-3.png" alt="">
315               </div>
316               <div class="content">
317                  <h3>Microsoft systems</h3>
318                  <p>Discover The Complete Range Of Microsoft Solutions.</p>
319               </div>
320            </div>
321         </div>
322      </section>
323      <section class="quote-section">
324         <div class="quote-container">
325            <div class="quote">"</div>
326            <p class="p-quote">In coded, the progress of the topics and the exercises are really good. It's so nice to practice on good story told tasks. Also if you are stuck, it is nice to have a broad range of coders around in the peer groups  that you can get the answers you are looking for.</p>
327            <div class="quote-img">
328               <img src="./Resources/Images/person-img.png" alt="">
329            </div>
330            <div class="person-name">Peter Gangland </div>
331            <div class="person-role">Director of business dev at <span>Microsoft</span></div>
332         </div>
333      </section>
334      <footer>
335         <div id="contact">
336            <h2>
337            Contact us</h5>
338            <h5>coded@peers.com</h5>
339            <h5>831-867-5309</h5>
340         </div>
341         <div id="copyright">
342            <h5>@copyright coded Enterprises 2022</h5>
343         </div>
344      </footer>
345   </body>
346</html>

1engine = pyttsx3.init('sapi5')
2voices = engine.getProperty('voices')
3engine.setProperty('voices', voices[0].id)
4
5
6def speak(audio):
7    engine.say(audio)
8    print(audio)
9    engine.runAndWait()
10

1engine = pyttsx3.init('sapi5')
2voices = engine.getProperty('voices')
3engine.setProperty('voices', voices[0].id)
4
5
6def speak(audio):
7    engine.say(audio)
8    print(audio)
9    engine.runAndWait()
10Process finished with exit code 0
11

1import requests
2from bs4 import BeautifulSoup
3
4URL = "https://aiml.events/"
5page = requests.get(URL)
6soup = BeautifulSoup(page.content, 'lxml')
7
8# Scrape Event Tags
9event_tags_list = []
10event_tag_div = soup.find_all('div', class_ = 'card-body')
11for event_div in event_tag_div:
12  event_span = event_div.find_all('span', class_  = 'badge badge-light badge-pill')
13  for event_tags in event_span:
14    print(event_tags.text)
15     
16

1import requests
2from bs4 import BeautifulSoup
3
4URL = "https://aiml.events/"
5page = requests.get(URL)
6soup = BeautifulSoup(page.content, 'lxml')
7
8# Scrape Event Tags
9event_tags_list = []
10event_tag_div = soup.find_all('div', class_ = 'card-body')
11for event_div in event_tag_div:
12  event_span = event_div.find_all('span', class_  = 'badge badge-light badge-pill')
13  for event_tags in event_span:
14    print(event_tags.text)
15     
16tag_list = ['Artificial Intelligence', 'Artificial Intelligence','Machine Learning', 'Healthcare', 'Artificial Intelligence','Public Sector' ] 
17

1import requests
2from bs4 import BeautifulSoup
3
4URL = "https://aiml.events/"
5page = requests.get(URL)
6soup = BeautifulSoup(page.content, 'lxml')
7
8# Scrape Event Tags
9event_tags_list = []
10event_tag_div = soup.find_all('div', class_ = 'card-body')
11for event_div in event_tag_div:
12  event_span = event_div.find_all('span', class_  = 'badge badge-light badge-pill')
13  for event_tags in event_span:
14    print(event_tags.text)
15     
16tag_list = ['Artificial Intelligence', 'Artificial Intelligence','Machine Learning', 'Healthcare', 'Artificial Intelligence','Public Sector' ] 
17tag_list = ['Artificial Intelligence', 'Artificial Intelligence,Machine Learning, Healthcare', 'Artificial Intelligence,Public Sector' ] 
18

1import Pdata from "../../api/projects.json";
2import p1 from "../../img/Project/PoleAnglais.png";
3import p2 from "../../img/Project/I-Art.png";
4import p3 from "../../img/Project/Hestia.png";
5import p4 from "../../img/Project/EvlV1.png";
6import p5 from "../../img/Project/Kelly.png";
7import p6 from "../../img/Project/EthLnyV2.png";
8import { Component } from "react";
9class Plist extends Component {
10  render() {
11    return (
12      <div
13        className="project-list"
14        data-aos="fade-right"
15        data-aos-duration="1200"
16      >
17        {Pdata.map((projectDetail, index) => {
18          return (
19            <div className="project-block">
20              <h2 className="project-title">{projectDetail.title}</h2>
21              <p className="date">{projectDetail.date}</p>
22              <p className="project-desc">{projectDetail.desc}</p>
23              <img src={projectDetail.id} alt="" />
24              <p className="madewith">made with {projectDetail.tags}</p>
25            </div>
26          );
27        })}
28      </div>
29    );
30  }
31}
32export default Plist;
33

1import Pdata from "../../api/projects.json";
2import p1 from "../../img/Project/PoleAnglais.png";
3import p2 from "../../img/Project/I-Art.png";
4import p3 from "../../img/Project/Hestia.png";
5import p4 from "../../img/Project/EvlV1.png";
6import p5 from "../../img/Project/Kelly.png";
7import p6 from "../../img/Project/EthLnyV2.png";
8import { Component } from "react";
9class Plist extends Component {
10  render() {
11    return (
12      <div
13        className="project-list"
14        data-aos="fade-right"
15        data-aos-duration="1200"
16      >
17        {Pdata.map((projectDetail, index) => {
18          return (
19            <div className="project-block">
20              <h2 className="project-title">{projectDetail.title}</h2>
21              <p className="date">{projectDetail.date}</p>
22              <p className="project-desc">{projectDetail.desc}</p>
23              <img src={projectDetail.id} alt="" />
24              <p className="madewith">made with {projectDetail.tags}</p>
25            </div>
26          );
27        })}
28      </div>
29    );
30  }
31}
32export default Plist;
33    [
34  {
35    "id": "p1",
36    "title": "Pole Anglais",
37    "date": "16/10/2019",
38    "desc": "This project was in association with Filip Zafirovski, my English teacher by the time who wanted students to get a source of inspiration by publishing articles and/or their work. It was my very first web project, and was kind of hard to pull off but I still enjoyed it.Since for the very first time i coded for a project and not myself.",
39    "tags": "Loads of crap"
40  },
41  {
42    "id": "p2",
43    "title": "Project I.Art",
44    "date": "3/07/2021",
45    "desc": "In France to go to college you have to get a diploma, which requires multiple exams to be validated. One of the subjects I had to do a presentation on was Art. I decided to create an idea around an Artificial Intelligence who would create art based on the likes and dislikes of the spectator. This panel is a website made for the occasion.",
46    "tags": "Html,Scss, & AOS librairie"
47  },
48  {
49    "id": "p3",
50    "title": "Hestia Real Estate",
51    "date": "18-26/10/2021",
52    "desc": "At the very start of my student life @hetic, They grouped student randomly to make a project. The subject of the project was to create an agency, a fake web-app and website that sells premium submarines to plus ultra rich people. For that project I designed the website of the agency, and the app for the complex.",
53    "tags": "Html & Scss"
54  },
55  {
56    "id": "p4",
57    "title": "EvL First Design",
58    "date": "30/10/2021",
59    "desc": "Before the design and dev of this portfolio, I had made a portfolio where I only putted my socials link. All of that because I had no idea of what to put on it. Even if I was satisfied with the first version it did not in any case represented the mood and emotion I wanted it to give. And so I gave birth to the actual design of the website on the 11/11/2021",
60    "tags": "Nextjs & Scss"
61  },
62  {
63    "id": "p5",
64    "title": "Kelly's Portfolio",
65    "date": "3/07/2021",
66    "desc": "Sometimes after arriving at my college, I met a freshly made friend who wanted to publish her portfolio. She knew how to design and do plenty others thing. To She didn't really like to code and was making her website with Wix. To which I proposed to remake her website by coding it myself.",
67    "tags": "VueJs & Scss"
68  },
69  {
70    "id": "p6",
71    "title": "EthLny V2",
72    "date": "11-12/11/2021",
73    "desc": "After doing the amazing portfolio of Kelly, I was kind of disappointed with my own. So I decided to remake a new design. Use a Random language, study the color psychology, searched a tagline. And TA-DA here it is, the website you're in right now is the result of 7 hours of researching, designing and coding and debugging.",
74    "tags": "ReactJs, Scss & AOS librairy"
75  }
76]
77

1string = 'machine learning ml is a type of artificial intelligence ai that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so machine12 learning algorithms use historical data as input to predict new output values machines learning is good'
2

1string = 'machine learning ml is a type of artificial intelligence ai that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so machine12 learning algorithms use historical data as input to predict new output values machines learning is good'
2tag = 'machine learning'
3

1string = 'machine learning ml is a type of artificial intelligence ai that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so machine12 learning algorithms use historical data as input to predict new output values machines learning is good'
2tag = 'machine learning'
3['machine learning', 'machine12 learning', 'machines learning']
4

1string = 'machine learning ml is a type of artificial intelligence ai that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so machine12 learning algorithms use historical data as input to predict new output values machines learning is good'
2tag = 'machine learning'
3['machine learning', 'machine12 learning', 'machines learning']
4tag_token = nltk.word_tokenize(tag)
5

1string = 'machine learning ml is a type of artificial intelligence ai that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so machine12 learning algorithms use historical data as input to predict new output values machines learning is good'
2tag = 'machine learning'
3['machine learning', 'machine12 learning', 'machines learning']
4tag_token = nltk.word_tokenize(tag)
5['machine learning', 'machine12 learning', 'machines learning']
6

1string = 'machine learning ml is a type of artificial intelligence ai that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so machine12 learning algorithms use historical data as input to predict new output values machines learning is good'
2tag = 'machine learning'
3['machine learning', 'machine12 learning', 'machines learning']
4tag_token = nltk.word_tokenize(tag)
5['machine learning', 'machine12 learning', 'machines learning']
6pattern = re.compile(r"(machine[\s0-9]+learning)",re.IGNORECASE)
7matches = pattern.findall(data)
8#[output]: ['machine learning', 'machine12 learning']
9

1string = 'machine learning ml is a type of artificial intelligence ai that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so machine12 learning algorithms use historical data as input to predict new output values machines learning is good'
2tag = 'machine learning'
3['machine learning', 'machine12 learning', 'machines learning']
4tag_token = nltk.word_tokenize(tag)
5['machine learning', 'machine12 learning', 'machines learning']
6pattern = re.compile(r"(machine[\s0-9]+learning)",re.IGNORECASE)
7matches = pattern.findall(data)
8#[output]: ['machine learning', 'machine12 learning']
9pattern = re.compile(r"(machine[\sA-Za-z]+learning)",re.IGNORECASE)
10matches = pattern.findall(data)
11#[output]: ['machine learning', 'machines learning']
12