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| [TGx]Downloaded from torrentgalaxy.to .txt |
585б |
| 0 |
153б |
| 001 Welcome.en.srt |
6.16Кб |
| 001 Welcome.mp4 |
42.59Мб |
| 002 Introduction.en.srt |
5.95Кб |
| 002 Introduction.mp4 |
35.75Мб |
| 003 DO NOT SKIP IT _ Download Working Files.html |
1.85Кб |
| 003 Sentiment-Classification-using-BERT.zip |
326.88Кб |
| 004 What is BERT.en.srt |
8.50Кб |
| 004 What is BERT.mp4 |
45.28Мб |
| 005 What is ktrain.en.srt |
6.82Кб |
| 005 What is ktrain.mp4 |
32.84Мб |
| 006 Going Deep Inside ktrain Package.en.srt |
6.86Кб |
| 006 Going Deep Inside ktrain Package.mp4 |
31.32Мб |
| 007 Notebook Setup.en.srt |
3.24Кб |
| 007 Notebook Setup.mp4 |
7.15Мб |
| 008 Must Read.html |
1.72Кб |
| 009 Installing ktrain.en.srt |
6.84Кб |
| 009 Installing ktrain.mp4 |
29.94Мб |
| 010 Loading Dataset.en.srt |
6.53Кб |
| 010 Loading Dataset.mp4 |
20.23Мб |
| 011 Train-Test Split and Preprocess with BERT.en.srt |
11.94Кб |
| 011 Train-Test Split and Preprocess with BERT.mp4 |
51.43Мб |
| 012 BERT Model Training.en.srt |
15.08Кб |
| 012 BERT Model Training.mp4 |
56.84Мб |
| 013 Testing Fine Tuned BERT Model.en.srt |
7.04Кб |
| 013 Testing Fine Tuned BERT Model.mp4 |
21.04Мб |
| 014 Saving and Loading Fine Tuned Model.en.srt |
10.51Кб |
| 014 Saving and Loading Fine Tuned Model.mp4 |
25.46Мб |
| 015 Fine-Tuning-BERT-for-Disaster-Tweets-Classification.zip |
2.55Мб |
| 015 Resources Folder.html |
926б |
| 016 BERT Intro - Disaster Tweets Dataset Understanding.en.srt |
14.16Кб |
| 016 BERT Intro - Disaster Tweets Dataset Understanding.mp4 |
109.80Мб |
| 017 Download Dataset.en.srt |
5.47Кб |
| 017 Download Dataset.mp4 |
29.73Мб |
| 018 Target Class Distribution.en.srt |
8.58Кб |
| 018 Target Class Distribution.mp4 |
31.48Мб |
| 019 Number of Characters Distribution in Tweets.en.srt |
14.58Кб |
| 019 Number of Characters Distribution in Tweets.mp4 |
83.53Мб |
| 020 Number of Words, Average Words Length, and Stop words Distribution in Tweets.en.srt |
8.35Кб |
| 020 Number of Words, Average Words Length, and Stop words Distribution in Tweets.mp4 |
41.00Мб |
| 021 Most and Least Common Words.en.srt |
8.73Кб |
| 021 Most and Least Common Words.mp4 |
43.39Мб |
| 022 One-Shot Data Cleaning.en.srt |
6.24Кб |
| 022 One-Shot Data Cleaning.mp4 |
32.03Мб |
| 023 Disaster Words Visualization with Word Cloud.en.srt |
5.95Кб |
| 023 Disaster Words Visualization with Word Cloud.mp4 |
42.16Мб |
| 024 Classification with TFIDF and SVM.en.srt |
9.79Кб |
| 024 Classification with TFIDF and SVM.mp4 |
44.18Мб |
| 025 Classification with Word2Vec and SVM.en.srt |
11.06Кб |
| 025 Classification with Word2Vec and SVM.mp4 |
52.89Мб |
| 026 Word Embeddings and Classification with Deep Learning Part 1.en.srt |
11.28Кб |
| 026 Word Embeddings and Classification with Deep Learning Part 1.mp4 |
52.87Мб |
| 027 Word Embeddings and Classification with Deep Learning Part 2.en.srt |
14.12Кб |
| 027 Word Embeddings and Classification with Deep Learning Part 2.mp4 |
73.57Мб |
| 028 BERT Model Building and Training.en.srt |
10.85Кб |
| 028 BERT Model Building and Training.mp4 |
55.15Мб |
| 029 BERT Model Evaluation.en.srt |
13.12Кб |
| 029 BERT Model Evaluation.mp4 |
58.43Мб |
| 030 DistilBERT-App.zip |
235.25Мб |
| 030 Sentiment-Classification-using-DistilBERT.zip |
10.48Кб |
| 030 What is DistilBERT_.en.srt |
12.53Кб |
| 030 What is DistilBERT_.mp4 |
74.05Мб |
| 031 Notebook Setup.en.srt |
7.07Кб |
| 031 Notebook Setup.mp4 |
24.38Мб |
| 032 Data Preparation.en.srt |
12.66Кб |
| 032 Data Preparation.mp4 |
54.61Мб |
| 033 DistilBERT Model Training.en.srt |
11.63Кб |
| 033 DistilBERT Model Training.mp4 |
41.60Мб |
| 034 Save Model at Google Drive.en.srt |
6.96Кб |
| 034 Save Model at Google Drive.mp4 |
22.76Мб |
| 035 Model Evaluation.en.srt |
4.57Кб |
| 035 Model Evaluation.mp4 |
14.91Мб |
| 036 Download Fine Tuned DistilBERT Model.en.srt |
2.04Кб |
| 036 Download Fine Tuned DistilBERT Model.mp4 |
4.89Мб |
| 037 Flask App Preparation.en.srt |
2.09Кб |
| 037 Flask App Preparation.mp4 |
6.24Мб |
| 038 Run Your First Flask Application.en.srt |
11.04Кб |
| 038 Run Your First Flask Application.mp4 |
32.38Мб |
| 039 Predict Sentiment at Your Local Machine.en.srt |
7.22Кб |
| 039 Predict Sentiment at Your Local Machine.mp4 |
21.88Мб |
| 040 Build Predict API.en.srt |
13.61Кб |
| 040 Build Predict API.mp4 |
56.18Мб |
| 041 Deploy DistilBERT Model at Your Local Machine.en.srt |
20.10Кб |
| 041 Deploy DistilBERT Model at Your Local Machine.mp4 |
69.47Мб |
| 042 Create AWS Account.en.srt |
9.35Кб |
| 042 Create AWS Account.mp4 |
36.62Мб |
| 043 Create Free Windows EC2 Instance.en.srt |
7.92Кб |
| 043 Create Free Windows EC2 Instance.mp4 |
47.68Мб |
| 044 Connect EC2 Instance from Windows 10.en.srt |
9.33Кб |
| 044 Connect EC2 Instance from Windows 10.mp4 |
52.49Мб |
| 045 Install Python on EC2 Windows 10.en.srt |
4.30Кб |
| 045 Install Python on EC2 Windows 10.mp4 |
15.78Мб |
| 046 Install TensorFlow 2 and KTRAIN.en.srt |
14.71Кб |
| 046 Install TensorFlow 2 and KTRAIN.mp4 |
66.57Мб |
| 047 Run Your First Flask Application on AWS EC2.en.srt |
10.46Кб |
| 047 Run Your First Flask Application on AWS EC2.mp4 |
29.13Мб |
| 048 Transfer DistilBERT Model to EC2 Flask Server.en.srt |
6.04Кб |
| 048 Transfer DistilBERT Model to EC2 Flask Server.mp4 |
24.44Мб |
| 049 Deploy ML Model on EC2 Server.en.srt |
17.67Кб |
| 049 Deploy ML Model on EC2 Server.mp4 |
71.00Мб |
| 050 Make Your ML Model Accessible to the World.en.srt |
17.73Кб |
| 050 Make Your ML Model Accessible to the World.mp4 |
66.81Мб |
| 051 Install Git Bash and Commander Terminal on Local Computer.en.srt |
10.69Кб |
| 051 Install Git Bash and Commander Terminal on Local Computer.mp4 |
40.92Мб |
| 052 Create AWS Account.en.srt |
9.35Кб |
| 052 Create AWS Account.mp4 |
36.63Мб |
| 053 Launch Ubuntu Machine on EC2.en.srt |
6.21Кб |
| 053 Launch Ubuntu Machine on EC2.mp4 |
31.39Мб |
| 054 Connect AWS Ubuntu (Linux) from Windows Computer.en.srt |
9.09Кб |
| 054 Connect AWS Ubuntu (Linux) from Windows Computer.mp4 |
32.55Мб |
| 055 Install PIP3 on AWS Ubuntu.en.srt |
7.56Кб |
| 055 Install PIP3 on AWS Ubuntu.mp4 |
44.61Мб |
| 056 Update and Upgrade Your Ubuntu Packages.en.srt |
3.47Кб |
| 056 Update and Upgrade Your Ubuntu Packages.mp4 |
19.87Мб |
| 057 Install TensorFlow 2 and KTRAIN.en.srt |
16.49Кб |
| 057 Install TensorFlow 2 and KTRAIN.mp4 |
93.58Мб |
| 058 Create Extra RAM from SSD by Memory Swapping.en.srt |
13.75Кб |
| 058 Create Extra RAM from SSD by Memory Swapping.mp4 |
83.72Мб |
| 059 Deploy DistilBERT ML Model on EC2 Ubuntu Machine.en.srt |
13.70Кб |
| 059 Deploy DistilBERT ML Model on EC2 Ubuntu Machine.mp4 |
44.20Мб |
| 060 NGINX Introduction.en.srt |
6.74Кб |
| 060 NGINX Introduction.mp4 |
36.62Мб |
| 060 NGINX-uWSGI-and-Flask-Installation-Guide-Jupyter-Notebook.zip |
86.60Кб |
| 061 Virtual Environment Setup.en.srt |
9.18Кб |
| 061 Virtual Environment Setup.mp4 |
57.70Мб |
| 062 Setting Up Flask Server.en.srt |
9.13Кб |
| 062 Setting Up Flask Server.mp4 |
50.74Мб |
| 063 Setting Up uWSGI Server.en.srt |
12.47Кб |
| 063 Setting Up uWSGI Server.mp4 |
101.74Мб |
| 064 Installing TensorFlow 2 and KTRAIN.en.srt |
8.92Кб |
| 064 Installing TensorFlow 2 and KTRAIN.mp4 |
56.08Мб |
| 065 Configuring uWSGI Server.en.srt |
5.99Кб |
| 065 Configuring uWSGI Server.mp4 |
32.86Мб |
| 066 Start API Services at System Startup.en.srt |
9.98Кб |
| 066 Start API Services at System Startup.mp4 |
58.14Мб |
| 067 Configuring NGINX with uWSGI, and Flask Server.en.srt |
13.53Кб |
| 067 Configuring NGINX with uWSGI, and Flask Server.mp4 |
91.78Мб |
| 068 Congrats! You Have Deployed ML Model in Production.en.srt |
24.55Кб |
| 068 Congrats! You Have Deployed ML Model in Production.mp4 |
84.90Мб |
| 069 FastText-App.zip |
18.54Мб |
| 069 FastText-Multi-Label-Text-Classification.zip |
4.49Кб |
| 069 NGINX-uWSGI-and-Flask-Installation-Guide-Jupyter-Notebook.zip |
95.39Кб |
| 069 What is Multi-Label Classification_.en.srt |
11.57Кб |
| 069 What is Multi-Label Classification_.mp4 |
32.74Мб |
| 070 FastText Research Paper Review.en.srt |
20.51Кб |
| 070 FastText Research Paper Review.mp4 |
160.06Мб |
| 071 Notebook Setup.en.srt |
9.95Кб |
| 071 Notebook Setup.mp4 |
45.76Мб |
| 072 Data Preparation.en.srt |
17.25Кб |
| 072 Data Preparation.mp4 |
67.42Мб |
| 073 FastText Model Training.en.srt |
9.76Кб |
| 073 FastText Model Training.mp4 |
38.62Мб |
| 074 FastText Model Evaluation and Saving at Google Drive.en.srt |
7.10Кб |
| 074 FastText Model Evaluation and Saving at Google Drive.mp4 |
19.93Мб |
| 075 Creating Fresh Ubuntu Machine.en.srt |
12.97Кб |
| 075 Creating Fresh Ubuntu Machine.mp4 |
59.30Мб |
| 076 Setting Python3 and PIP3 Alias.en.srt |
9.81Кб |
| 076 Setting Python3 and PIP3 Alias.mp4 |
49.32Мб |
| 077 Creating 4GB Extra RAM by Memory Swapping.en.srt |
5.58Кб |
| 077 Creating 4GB Extra RAM by Memory Swapping.mp4 |
37.03Мб |
| 078 Making Your Server Ready.en.srt |
9.73Кб |
| 078 Making Your Server Ready.mp4 |
76.49Мб |
| 079 Preparing Prediction APIs.en.srt |
19.96Кб |
| 079 Preparing Prediction APIs.mp4 |
80.76Мб |
| 080 Testing Prediction API at Local Machine.en.srt |
9.62Кб |
| 080 Testing Prediction API at Local Machine.mp4 |
40.22Мб |
| 081 Testing Prediction API at AWS Ubuntu Machine.en.srt |
13.54Кб |
| 081 Testing Prediction API at AWS Ubuntu Machine.mp4 |
77.45Мб |
| 082 Configuring uWSGI Server.en.srt |
9.62Кб |
| 082 Configuring uWSGI Server.mp4 |
58.27Мб |
| 083 Deploy FastText Model in Production with NGINX, uWSGI, and Flask.en.srt |
11.64Кб |
| 083 Deploy FastText Model in Production with NGINX, uWSGI, and Flask.mp4 |
58.62Мб |
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