▲
0
0

report

Udemy - Deployment of Machine Learning Models in Production | Python

seeders: 4
leechers: 1
Download torrent
Added 5 years ago by tutsnode in Other
Download Fast Safe Anonymous
movies, software, shows...

Files

Udemy - Deployment of Machine Learning Models in Production | Python (Size: 4.1 GB)
  0 102 B
  1 385.5 KB
  001 Welcome.en.srt 6.2 KB
  001 Welcome.mp4 42.6 MB
  002 Introduction.mp4 35.8 MB
  2 203.9 KB
  002 Introduction.en.srt 6 KB
  003 DO NOT SKIP IT _ Download Working Files.html 1.8 KB
  003 Sentiment-Classification-using-BERT.zip 326.9 KB
  3 262.3 KB
  4 425.4 KB
  004 What is BERT.en.srt 8.5 KB
  004 What is BERT.mp4 45.3 MB
  5 224.5 KB
  005 What is ktrain.en.srt 6.8 KB
  005 What is ktrain.mp4 32.8 MB
  006 Going Deep Inside ktrain Package.en.srt 6.9 KB
  6 98.7 KB
  006 Going Deep Inside ktrain Package.mp4 31.3 MB
  7 287.2 KB
  007 Notebook Setup.en.srt 3.2 KB
  007 Notebook Setup.mp4 7.2 MB
  008 Must Read.html 1.7 KB
  8 483.7 KB
  009 Installing ktrain.en.srt 6.8 KB
  009 Installing ktrain.mp4 29.9 MB
  9 244.5 KB
  010 Loading Dataset.en.srt 6.5 KB
  10 562.3 KB
  010 Loading Dataset.mp4 20.2 MB
  011 Train-Test Split and Preprocess with BERT.en.srt 11.9 KB
  011 Train-Test Split and Preprocess with BERT.mp4 51.4 MB
  11 524.5 KB
  12 969.5 KB
  012 BERT Model Training.en.srt 15.1 KB
  012 BERT Model Training.mp4 56.8 MB
  013 Testing Fine Tuned BERT Model.mp4 21 MB
  13 438.7 KB
  013 Testing Fine Tuned BERT Model.en.srt 7 KB
  014 Saving and Loading Fine Tuned Model.en.srt 10.5 KB
  014 Saving and Loading Fine Tuned Model.mp4 25.5 MB
  14 1.9 KB
  015 Resources Folder.html 921 B
  15 544.1 KB
  015 Fine-Tuning-BERT-for-Disaster-Tweets-Classification.zip 2.5 MB
  016 BERT Intro - Disaster Tweets Dataset Understanding.en.srt 14.2 KB
  16 594.7 KB
  016 BERT Intro - Disaster Tweets Dataset Understanding.mp4 109.8 MB
  17 197.7 KB
  017 Download Dataset.en.srt 5.5 KB
  017 Download Dataset.mp4 29.7 MB
  018 Target Class Distribution.mp4 31.5 MB
  18 436.3 KB
  018 Target Class Distribution.en.srt 8.6 KB
  19 717 KB
  019 Number of Characters Distribution in Tweets.en.srt 14.6 KB
  019 Number of Characters Distribution in Tweets.mp4 83.5 MB
  020 Number of Words, Average Words Length, and Stop words Distribution in Tweets.en.srt 8.4 KB
  20 384.8 KB
  020 Number of Words, Average Words Length, and Stop words Distribution in Tweets.mp4 41 MB
  021 Most and Least Common Words.en.srt 8.7 KB
  021 Most and Least Common Words.mp4 43.4 MB
  21 581.3 KB
  22 743.9 KB
  022 One-Shot Data Cleaning.en.srt 6.2 KB
  022 One-Shot Data Cleaning.mp4 32 MB
  023 Disaster Words Visualization with Word Cloud.en.srt 5.9 KB
  23 880 KB
  023 Disaster Words Visualization with Word Cloud.mp4 42.2 MB
  024 Classification with TFIDF and SVM.mp4 44.2 MB
  24 311.1 KB
  024 Classification with TFIDF and SVM.en.srt 9.8 KB
  25 166.5 KB
  025 Classification with Word2Vec and SVM.en.srt 11.1 KB
  025 Classification with Word2Vec and SVM.mp4 52.9 MB
  026 Word Embeddings and Classification with Deep Learning Part 1.en.srt 11.3 KB
  026 Word Embeddings and Classification with Deep Learning Part 1.mp4 52.9 MB
  26 838.5 KB
  027 Word Embeddings and Classification with Deep Learning Part 2.en.srt 14.1 KB
  027 Word Embeddings and Classification with Deep Learning Part 2.mp4 73.6 MB
  27 944.4 KB
  28 875.2 KB
  028 BERT Model Building and Training.en.srt 10.9 KB
  028 BERT Model Building and Training.mp4 55.1 MB
  29 402.6 KB
  029 BERT Model Evaluation.en.srt 13.1 KB
  029 BERT Model Evaluation.mp4 58.4 MB
  030 DistilBERT-App.zip 235.2 MB
  030 Sentiment-Classification-using-DistilBERT.zip 10.5 KB
  030 What is DistilBERT_.mp4 74.1 MB
  30 108 KB
  030 What is DistilBERT_.en.srt 12.5 KB
  031 Notebook Setup.en.srt 7.1 KB
  31 130.7 KB
  031 Notebook Setup.mp4 24.4 MB
  032 Data Preparation.mp4 54.6 MB
  32 525.2 KB
  032 Data Preparation.en.srt 12.7 KB
  33 585.2 KB
  033 DistilBERT Model Training.en.srt 11.6 KB
  033 DistilBERT Model Training.mp4 41.6 MB
  34 269.4 KB
  034 Save Model at Google Drive.en.srt 7 KB
  034 Save Model at Google Drive.mp4 22.8 MB
  035 Model Evaluation.en.srt 4.6 KB
  35 700.7 KB
  035 Model Evaluation.mp4 14.9 MB
  036 Download Fine Tuned DistilBERT Model.en.srt 2 KB
  036 Download Fine Tuned DistilBERT Model.mp4 4.9 MB
  36 332.1 KB
  37 248.1 KB
  037 Flask App Preparation.en.srt 2.1 KB
  037 Flask App Preparation.mp4 6.2 MB
  038 Run Your First Flask Application.en.srt 11 KB
  38 738.3 KB
  038 Run Your First Flask Application.mp4 32.4 MB
  39 397.9 KB
  039 Predict Sentiment at Your Local Machine.en.srt 7.2 KB
  039 Predict Sentiment at Your Local Machine.mp4 21.9 MB
  040 Build Predict API.en.srt 13.6 KB
  040 Build Predict API.mp4 56.2 MB
  40 819.9 KB
  41 835.9 KB
  041 Deploy DistilBERT Model at Your Local Machine.en.srt 20.1 KB
  041 Deploy DistilBERT Model at Your Local Machine.mp4 69.5 MB
  042 Create AWS Account.en.srt 9.4 KB
  042 Create AWS Account.mp4 36.6 MB
  42 628.8 KB
  043 Create Free Windows EC2 Instance.en.srt 7.9 KB
  043 Create Free Windows EC2 Instance.mp4 47.7 MB
  43 414.7 KB
  44 863.5 KB
  044 Connect EC2 Instance from Windows 10.en.srt 9.3 KB
  044 Connect EC2 Instance from Windows 10.mp4 52.5 MB
  045 Install Python on EC2 Windows 10.en.srt 4.3 KB
  045 Install Python on EC2 Windows 10.mp4 15.8 MB
  45 413.5 KB
  46 0 B
  046 Install TensorFlow 2 and KTRAIN.en.srt 14.7 KB
  046 Install TensorFlow 2 and KTRAIN.mp4 66.6 MB
  047 Run Your First Flask Application on AWS EC2.en.srt 10.5 KB
  047 Run Your First Flask Application on AWS EC2.mp4 29.1 MB
  47 83.2 KB
  48 802.8 KB
  048 Transfer DistilBERT Model to EC2 Flask Server.en.srt 6 KB
  048 Transfer DistilBERT Model to EC2 Flask Server.mp4 24.4 MB
  049 Deploy ML Model on EC2 Server.en.srt 17.7 KB
  049 Deploy ML Model on EC2 Server.mp4 71 MB
  49 387.5 KB
  50 993.2 KB
  050 Make Your ML Model Accessible to the World.en.srt 17.7 KB
  050 Make Your ML Model Accessible to the World.mp4 66.8 MB
  51 382.2 KB
  051 Install Git Bash and Commander Terminal on Local Computer.en.srt 10.7 KB
  051 Install Git Bash and Commander Terminal on Local Computer.mp4 40.9 MB
  52 387.7 KB
  052 Create AWS Account.en.srt 9.4 KB
  052 Create AWS Account.mp4 36.6 MB
  53 390.2 KB
  053 Launch Ubuntu Machine on EC2.en.srt 6.2 KB
  053 Launch Ubuntu Machine on EC2.mp4 31.4 MB
  054 Connect AWS Ubuntu (Linux) from Windows Computer.en.srt 9.1 KB
  054 Connect AWS Ubuntu (Linux) from Windows Computer.mp4 32.5 MB
  54 253.5 KB
  055 Install PIP3 on AWS Ubuntu.mp4 44.6 MB
  55 145.2 KB
  055 Install PIP3 on AWS Ubuntu.en.srt 7.6 KB
  56 167.7 KB
  056 Update and Upgrade Your Ubuntu Packages.en.srt 3.5 KB
  056 Update and Upgrade Your Ubuntu Packages.mp4 19.9 MB
  057 Install TensorFlow 2 and KTRAIN.en.srt 16.5 KB
  057 Install TensorFlow 2 and KTRAIN.mp4 93.6 MB
  57 265.8 KB
  058 Create Extra RAM from SSD by Memory Swapping.en.srt 13.7 KB
  058 Create Extra RAM from SSD by Memory Swapping.mp4 83.7 MB
  58 462.7 KB
  059 Deploy DistilBERT ML Model on EC2 Ubuntu Machine.en.srt 13.7 KB
  059 Deploy DistilBERT ML Model on EC2 Ubuntu Machine.mp4 44.2 MB
  59 633.6 KB
  60 993.3 KB
  060 NGINX Introduction.en.srt 6.7 KB
  060 NGINX Introduction.mp4 36.6 MB
  060 NGINX-uWSGI-and-Flask-Installation-Guide-Jupyter-Notebook.zip 86.6 KB
  061 Virtual Environment Setup.en.srt 9.2 KB
  061 Virtual Environment Setup.mp4 57.7 MB
  61 536.5 KB
  062 Setting Up Flask Server.en.srt 9.1 KB
  062 Setting Up Flask Server.mp4 50.7 MB
  62 625.6 KB
  063 Setting Up uWSGI Server.en.srt 12.5 KB
  063 Setting Up uWSGI Server.mp4 101.7 MB
  63 700.1 KB
  064 Installing TensorFlow 2 and KTRAIN.mp4 56.1 MB
  64 57 KB
  064 Installing TensorFlow 2 and KTRAIN.en.srt 8.9 KB
  65 278.8 KB
  065 Configuring uWSGI Server.en.srt 6 KB
  065 Configuring uWSGI Server.mp4 32.9 MB
  66 889.3 KB
  066 Start API Services at System Startup.en.srt 10 KB
  066 Start API Services at System Startup.mp4 58.1 MB
  67 552.9 KB
  067 Configuring NGINX with uWSGI, and Flask Server.en.srt 13.5 KB
  067 Configuring NGINX with uWSGI, and Flask Server.mp4 91.8 MB
  068 Congrats! You Have Deployed ML Model in Production.en.srt 24.5 KB
  068 Congrats! You Have Deployed ML Model in Production.mp4 84.9 MB
  68 571.1 KB
  069 NGINX-uWSGI-and-Flask-Installation-Guide-Jupyter-Notebook.zip 95.4 KB
  069 What is Multi-Label Classification_.en.srt 11.6 KB
  69 639.2 KB
  069 FastText-App.zip 18.5 MB
  069 FastText-Multi-Label-Text-Classification.zip 4.5 KB
  069 What is Multi-Label Classification_.mp4 32.7 MB
  70 246.9 KB
  070 FastText Research Paper Review.en.srt 20.5 KB
  070 FastText Research Paper Review.mp4 160.1 MB
  071 Notebook Setup.mp4 45.8 MB
  71 125.8 KB
  071 Notebook Setup.en.srt 9.9 KB
  72 980.1 KB
  072 Data Preparation.en.srt 17.3 KB
  072 Data Preparation.mp4 67.4 MB
  073 FastText Model Training.en.srt 9.8 KB
  073 FastText Model Training.mp4 38.6 MB
  73 792.1 KB
  074 FastText Model Evaluation and Saving at Google Drive.en.srt 7.1 KB
  074 FastText Model Evaluation and Saving at Google Drive.mp4 19.9 MB
  74 73.3 KB
  75 131.4 KB
  075 Creating Fresh Ubuntu Machine.en.srt 13 KB
  075 Creating Fresh Ubuntu Machine.mp4 59.3 MB
  76 475 KB
  076 Setting Python3 and PIP3 Alias.en.srt 9.8 KB
  076 Setting Python3 and PIP3 Alias.mp4 49.3 MB
  77 223.7 KB
  077 Creating 4GB Extra RAM by Memory Swapping.en.srt 5.6 KB
  077 Creating 4GB Extra RAM by Memory Swapping.mp4 37 MB
  078 Making Your Server Ready.en.srt 9.7 KB
  078 Making Your Server Ready.mp4 76.5 MB
  78 95.4 KB
  079 Preparing Prediction APIs.en.srt 20 KB
  79 868.3 KB
  079 Preparing Prediction APIs.mp4 80.8 MB
  080 Testing Prediction API at Local Machine.en.srt 9.6 KB
  080 Testing Prediction API at Local Machine.mp4 40.2 MB
  081 Testing Prediction API at AWS Ubuntu Machine.en.srt 13.5 KB
  081 Testing Prediction API at AWS Ubuntu Machine.mp4 77.5 MB
  082 Configuring uWSGI Server.en.srt 9.6 KB
  082 Configuring uWSGI Server.mp4 58.3 MB
  083 Deploy FastText Model in Production with NGINX, uWSGI, and Flask.en.srt 11.6 KB
  083 Deploy FastText Model in Production with NGINX, uWSGI, and Flask.mp4 58.6 MB
  TutsNode.com.txt 102 B
  [TGx]Downloaded from torrentgalaxy.to .txt 614 B
  80 776.8 KB
  81 110 KB
  ▲ 255 total files

Description



Description

Are you ready to kickstart your Advanced NLP course? Are you ready to deploy your machine learning models in production at AWS? You will learn each and every steps on how to build and deploy your ML model on a robust and secure server at AWS.

Prior knowledge of python and Data Science is assumed. If you are AN absolute beginner in Data Science, please do not take this course. This course is made for medium or advanced level of Data Scientist.

What is BERT?

BERT is a method of pre-training language representations, meaning that we train a general-purpose “language understanding” model on a large text corpus (like Wikipedia), and then use that model for downstream NLP tasks that we care about (like question answering). BERT outperforms previous methods because it is the first unsupervised, deeply bidirectional system for pre-training NLP.

Unsupervised means that BERT was trained using only a plain text corpus, which is important because an enormous amount of plain text data is publicly available on the web in many languages.

Why is BERT so revolutionary?

Not only is it a framework that has been pre-trained with the biggest data set ever used, but it is also remarkably easy to adapt to different NLP applications, by adding additional output layers. This allows users to create sophisticated and precise models to carry out a wide variety of NLP tasks.

Here is what you will learn in this course

Notebook Setup and What is BERT.
Data Preprocessing.
BERT Model Building and Training.
BERT Model Evaluation and Saving.
DistilBERT Model Fine Tuning and Deployment
Deploy Your ML Model at AWS with Flask Server
Deploy Your Model at Both Windows and Ubuntu Machine
And so much more!

All these things will be done on Google Colab which means it doesn’t matter what processor and computer you have. It is super easy to use and plus point is that you have Free GPU to use in your notebook.
Who this course is for:

AI Students eager to learn advanced techniques of text processing
Data Science enthusiastic to build end-to-end NLP Application
Anyone wants to strengthen NLP skills
Anyone want to deploy ML Model in Production
Data Scientists who want to learn Production Ready ML Model Deployment

Requirements

Introductory knowledge of NLP
Comfortable in Python, Keras, and TensorFlow 2
Basic Elementary Mathematics

Last Updated 1/2021

Related Torrents

torrent name size uploader age seed leech
Udemy - Mastering Web Deployment with CI - CD Automation Posted by freecoursewb in Other
1.7 GB freecoursewb 1 month 0 0
Udemy - Complete Node.js Developer 2026 - APIs, Projects and Deployment Posted by freecoursewb in Other
2.1 GB freecoursewb 2 months 12 3
Udemy - Edge AI with SLMs - Fine-Tuning and Local Deployment Posted by freecoursewb in Other
1.3 GB freecoursewb 3 months 0 0
Udemy - Zigbee Application Development - From Basics to Deployment Posted by freecoursewb in Other
854 MB freecoursewb 7 months 0 0
Udemy - Integration and Deployment of GenAI Models Posted by freecoursewb in Other
1.5 GB freecoursewb 1 year 8 3