Deployment of Machine Learning Models in Production Python | F2BF4C45530F1331A1BAA6FA7C699E08A23D9EBA

Deployment of Machine Learning Models in Production Python

Name	Deployment of Machine Learning Models in Production Python	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	4.4 GB
Total Files	255
Last Seen	2025-05-23 23:44
Hash	F2BF4C45530F1331A1BAA6FA7C699E08A23D9EBA

/.../03 DistilBERT _ Faster and Cheaper BERT model from Hugging Face/
030 DistilBERT-App.zip	246.7 MB
041 Deploy DistilBERT Model at Your Local Machine.en.srt	20.6 KB
037 Flask App Preparation.en.srt	2.1 KB
040 Build Predict API.en.srt	13.9 KB
032 Data Preparation.en.srt	13.0 KB
030 What is DistilBERT_.en.srt	12.8 KB
033 DistilBERT Model Training.en.srt	11.9 KB
038 Run Your First Flask Application.en.srt	11.3 KB
030 Sentiment-Classification-using-DistilBERT.zip	10.7 KB
039 Predict Sentiment at Your Local Machine.en.srt	7.4 KB
031 Notebook Setup.en.srt	7.2 KB
034 Save Model at Google Drive.en.srt	7.1 KB
036 Download Fine Tuned DistilBERT Model.en.srt	2.1 KB
035 Model Evaluation.en.srt	4.7 KB
030 What is DistilBERT_.mp4	77.7 MB
041 Deploy DistilBERT Model at Your Local Machine.mp4	72.8 MB
040 Build Predict API.mp4	58.9 MB
032 Data Preparation.mp4	57.3 MB
033 DistilBERT Model Training.mp4	43.6 MB
038 Run Your First Flask Application.mp4	34.0 MB
031 Notebook Setup.mp4	25.6 MB
034 Save Model at Google Drive.mp4	23.9 MB
039 Predict Sentiment at Your Local Machine.mp4	22.9 MB
035 Model Evaluation.mp4	15.6 MB
037 Flask App Preparation.mp4	6.5 MB
036 Download Fine Tuned DistilBERT Model.mp4	5.1 MB
/
TutsNode.com.txt	0.1 KB
[TGx]Downloaded from torrentgalaxy.to .txt	0.6 KB
/.../01 BERT _ Sentiment Prediction _ Multi Class Prediction Problem/
003 Sentiment-Classification-using-BERT.zip	334.7 KB
003 DO NOT SKIP IT _ Download Working Files.html	1.9 KB
012 BERT Model Training.en.srt	15.4 KB
008 Must Read.html	1.8 KB
011 Train-Test Split and Preprocess with BERT.en.srt	12.2 KB
014 Saving and Loading Fine Tuned Model.en.srt	10.8 KB
004 What is BERT.en.srt	8.7 KB
013 Testing Fine Tuned BERT Model.en.srt	7.2 KB
006 Going Deep Inside ktrain Package.en.srt	7.0 KB
009 Installing ktrain.en.srt	7.0 KB
005 What is ktrain.en.srt	7.0 KB
010 Loading Dataset.en.srt	6.7 KB
001 Welcome.en.srt	6.3 KB
002 Introduction.en.srt	6.1 KB
007 Notebook Setup.en.srt	3.3 KB
012 BERT Model Training.mp4	59.6 MB
011 Train-Test Split and Preprocess with BERT.mp4	53.9 MB
004 What is BERT.mp4	47.5 MB
001 Welcome.mp4	44.7 MB
002 Introduction.mp4	37.5 MB
005 What is ktrain.mp4	34.4 MB
006 Going Deep Inside ktrain Package.mp4	32.8 MB
009 Installing ktrain.mp4	31.4 MB
014 Saving and Loading Fine Tuned Model.mp4	26.7 MB
013 Testing Fine Tuned BERT Model.mp4	22.1 MB
010 Loading Dataset.mp4	21.2 MB
007 Notebook Setup.mp4	7.5 MB
/.../07 Multi-Label Classification _ Deploy Facebook's FastText NLP Model in Production/
069 NGINX-uWSGI-and-Flask-Installation-Guide-Jupyter-Notebook.zip	97.7 KB
070 FastText Research Paper Review.en.srt	21.0 KB
079 Preparing Prediction APIs.en.srt	20.4 KB
072 Data Preparation.en.srt	17.7 KB
070 FastText Research Paper Review.mp4	167.8 MB
081 Testing Prediction API at AWS Ubuntu Machine.en.srt	13.9 KB
075 Creating Fresh Ubuntu Machine.en.srt	13.3 KB
083 Deploy FastText Model in Production with NGINX, uWSGI, and Flask.en.srt	11.9 KB
069 What is Multi-Label Classification_.en.srt	11.8 KB
071 Notebook Setup.en.srt	10.2 KB
076 Setting Python3 and PIP3 Alias.en.srt	10.1 KB
073 FastText Model Training.en.srt	10.0 KB
078 Making Your Server Ready.en.srt	10.0 KB
080 Testing Prediction API at Local Machine.en.srt	9.9 KB
082 Configuring uWSGI Server.en.srt	9.8 KB
074 FastText Model Evaluation and Saving at Google Drive.en.srt	7.3 KB
077 Creating 4GB Extra RAM by Memory Swapping.en.srt	5.7 KB
069 FastText-Multi-Label-Text-Classification.zip	4.6 KB
079 Preparing Prediction APIs.mp4	84.7 MB
081 Testing Prediction API at AWS Ubuntu Machine.mp4	81.2 MB
078 Making Your Server Ready.mp4	80.2 MB
072 Data Preparation.mp4	70.7 MB
075 Creating Fresh Ubuntu Machine.mp4	62.2 MB
083 Deploy FastText Model in Production with NGINX, uWSGI, and Flask.mp4	61.5 MB
082 Configuring uWSGI Server.mp4	61.1 MB
076 Setting Python3 and PIP3 Alias.mp4	51.7 MB
071 Notebook Setup.mp4	48.0 MB
080 Testing Prediction API at Local Machine.mp4	42.2 MB
073 FastText Model Training.mp4	40.5 MB
077 Creating 4GB Extra RAM by Memory Swapping.mp4	38.8 MB
069 What is Multi-Label Classification_.mp4	34.3 MB
074 FastText Model Evaluation and Saving at Google Drive.mp4	20.9 MB
069 FastText-App.zip	19.4 MB
/.../06 Deploy Robust and Secure Production Server with NGINX, uWSGI, and Flask/
060 NGINX-uWSGI-and-Flask-Installation-Guide-Jupyter-Notebook.zip	88.7 KB
068 Congrats! You Have Deployed ML Model in Production.en.srt	25.1 KB
067 Configuring NGINX with uWSGI, and Flask Server.en.srt	13.9 KB
063 Setting Up uWSGI Server.en.srt	12.8 KB
066 Start API Services at System Startup.en.srt	10.2 KB
061 Virtual Environment Setup.en.srt	9.4 KB
062 Setting Up Flask Server.en.srt	9.3 KB
064 Installing TensorFlow 2 and KTRAIN.en.srt	9.1 KB
060 NGINX Introduction.en.srt	6.9 KB
065 Configuring uWSGI Server.en.srt	6.1 KB
063 Setting Up uWSGI Server.mp4	106.7 MB
067 Configuring NGINX with uWSGI, and Flask Server.mp4	96.2 MB
068 Congrats! You Have Deployed ML Model in Production.mp4	89.0 MB
066 Start API Services at System Startup.mp4	61.0 MB
061 Virtual Environment Setup.mp4	60.5 MB
064 Installing TensorFlow 2 and KTRAIN.mp4	58.8 MB
062 Setting Up Flask Server.mp4	53.2 MB
060 NGINX Introduction.mp4	38.4 MB
065 Configuring uWSGI Server.mp4	34.5 MB
/.../04 Deploy Your DistilBERT ML Model at AWS EC2 Windows Machine with Flask/
050 Make Your ML Model Accessible to the World.en.srt	18.2 KB
049 Deploy ML Model on EC2 Server.en.srt	18.1 KB
046 Install TensorFlow 2 and KTRAIN.en.srt	15.1 KB
047 Run Your First Flask Application on AWS EC2.en.srt	10.7 KB
042 Create AWS Account.en.srt	9.6 KB
044 Connect EC2 Instance from Windows 10.en.srt	9.6 KB
043 Create Free Windows EC2 Instance.en.srt	8.1 KB
048 Transfer DistilBERT Model to EC2 Flask Server.en.srt	6.2 KB
045 Install Python on EC2 Windows 10.en.srt	4.4 KB
049 Deploy ML Model on EC2 Server.mp4	74.4 MB
050 Make Your ML Model Accessible to the World.mp4	70.1 MB
046 Install TensorFlow 2 and KTRAIN.mp4	69.8 MB
044 Connect EC2 Instance from Windows 10.mp4	55.0 MB
043 Create Free Windows EC2 Instance.mp4	50.0 MB
042 Create AWS Account.mp4	38.4 MB
047 Run Your First Flask Application on AWS EC2.mp4	30.5 MB
048 Transfer DistilBERT Model to EC2 Flask Server.mp4	25.6 MB
045 Install Python on EC2 Windows 10.mp4	16.5 MB
/.../05 Deploy Your DistilBERT ML Model at AWS Ubuntu (Linux) Machine with Flask/
057 Install TensorFlow 2 and KTRAIN.en.srt	16.9 KB
058 Create Extra RAM from SSD by Memory Swapping.en.srt	14.1 KB
059 Deploy DistilBERT ML Model on EC2 Ubuntu Machine.en.srt	14.0 KB
051 Install Git Bash and Commander Terminal on Local Computer.en.srt	10.9 KB
052 Create AWS Account.en.srt	9.6 KB
054 Connect AWS Ubuntu (Linux) from Windows Computer.en.srt	9.3 KB
055 Install PIP3 on AWS Ubuntu.en.srt	7.7 KB
053 Launch Ubuntu Machine on EC2.en.srt	6.4 KB
056 Update and Upgrade Your Ubuntu Packages.en.srt	3.6 KB
057 Install TensorFlow 2 and KTRAIN.mp4	98.1 MB
058 Create Extra RAM from SSD by Memory Swapping.mp4	87.8 MB
055 Install PIP3 on AWS Ubuntu.mp4	46.8 MB
059 Deploy DistilBERT ML Model on EC2 Ubuntu Machine.mp4	46.3 MB
051 Install Git Bash and Commander Terminal on Local Computer.mp4	42.9 MB
052 Create AWS Account.mp4	38.4 MB
054 Connect AWS Ubuntu (Linux) from Windows Computer.mp4	34.1 MB
053 Launch Ubuntu Machine on EC2.mp4	32.9 MB
056 Update and Upgrade Your Ubuntu Packages.mp4	20.8 MB
/.../02 Fine Tuning BERT for Disaster Tweets Classification/
019 Number of Characters Distribution in Tweets.en.srt	14.9 KB
016 BERT Intro - Disaster Tweets Dataset Understanding.en.srt	14.5 KB
027 Word Embeddings and Classification with Deep Learning Part 2.en.srt	14.5 KB
015 Resources Folder.html	0.9 KB
029 BERT Model Evaluation.en.srt	13.4 KB
026 Word Embeddings and Classification with Deep Learning Part 1.en.srt	11.6 KB
025 Classification with Word2Vec and SVM.en.srt	11.3 KB
028 BERT Model Building and Training.en.srt	11.1 KB
024 Classification with TFIDF and SVM.en.srt	10.0 KB
021 Most and Least Common Words.en.srt	8.9 KB
018 Target Class Distribution.en.srt	8.8 KB
020 Number of Words, Average Words Length, and Stop words Distribution in Tweets.en.srt	8.6 KB
022 One-Shot Data Cleaning.en.srt	6.4 KB
023 Disaster Words Visualization with Word Cloud.en.srt	6.1 KB
017 Download Dataset.en.srt	5.6 KB
016 BERT Intro - Disaster Tweets Dataset Understanding.mp4	115.1 MB
019 Number of Characters Distribution in Tweets.mp4	87.6 MB
027 Word Embeddings and Classification with Deep Learning Part 2.mp4	77.1 MB
029 BERT Model Evaluation.mp4	61.3 MB
028 BERT Model Building and Training.mp4	57.8 MB
025 Classification with Word2Vec and SVM.mp4	55.5 MB
026 Word Embeddings and Classification with Deep Learning Part 1.mp4	55.4 MB
024 Classification with TFIDF and SVM.mp4	46.3 MB
021 Most and Least Common Words.mp4	45.5 MB
023 Disaster Words Visualization with Word Cloud.mp4	44.2 MB
020 Number of Words, Average Words Length, and Stop words Distribution in Tweets.mp4	43.0 MB
022 One-Shot Data Cleaning.mp4	33.6 MB
018 Target Class Distribution.mp4	33.0 MB
017 Download Dataset.mp4	31.2 MB
015 Fine-Tuning-BERT-for-Disaster-Tweets-Classification.zip	2.7 MB
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