[DesireCourse.Net] Udemy - Deploy Machine Learning & NLP Models with Dockers (DevOps)

Creation Time	April 10, 2025, 6:02 a.m.
Last Access Time	April 7, 2026, 12:15 p.m.
File Size	2.2 GB
Keywords	Dockers NLP Deploy Models DesireCourse - DevOps Udemy Machine Learning Net with
Total Requests	213
Total Files	129
Magnet Link	Please wait ...
	Download (Magnet Link) Play (Watch Online)

7. Building NLP based Text Clustering application/5. Preparing the excel output.mp4 108.8 MB
7. Building NLP based Text Clustering application/3. Converting unstructured to structured data.mp4 95.7 MB
8. API for image recognition with deep learning/4. Building the deep learning model.mp4 93.1 MB
7. Building NLP based Text Clustering application/2. Stemming & Lemmatization for cleaner text.mp4 90.9 MB
8. API for image recognition with deep learning/3. Preparing the input images.mp4 89.5 MB
6. Building a production grade Docker application/5. Running and debugging a docker container in production.mp4 86.0 MB
4. Exposing a Random Forest Machine Learning service as an API/8. Flasgger for autogenerating UI.mp4 85.2 MB
7. Building NLP based Text Clustering application/4. KMeans Clustering.mp4 82.2 MB
5. Writing and building the Dockerfile/8. Running the Random Forest model on Docker.mp4 78.7 MB
8. API for image recognition with deep learning/7. Flask API wrapper for making predictions.mp4 78.3 MB
7. Building NLP based Text Clustering application/8. Final output with charts.mp4 76.4 MB
4. Exposing a Random Forest Machine Learning service as an API/7. Providing file input to Flask API.mp4 75.7 MB
7. Building NLP based Text Clustering application/7. Finding top keywords for kmeans clusters.mp4 75.0 MB
5. Writing and building the Dockerfile/7. Building the docker image.mp4 74.8 MB
8. API for image recognition with deep learning/2. Visualizing the input images.mp4 68.3 MB
7. Building NLP based Text Clustering application/6. Making the output Downloadable.mp4 65.5 MB
6. Building a production grade Docker application/3. Configuring the WSGI file.mp4 62.4 MB
6. Building a production grade Docker application/4. Writing a production grade Dockerfile.mp4 61.4 MB
4. Exposing a Random Forest Machine Learning service as an API/5. Exposing the Random Forest model as a Flask API.mp4 54.3 MB
3. Flask basics/5. POST request with Flask.mp4 48.0 MB
5. Writing and building the Dockerfile/6. Writing the Dockerfile.mp4 46.0 MB
4. Exposing a Random Forest Machine Learning service as an API/3. Training the Random Forest model.mp4 45.8 MB
4. Exposing a Random Forest Machine Learning service as an API/6. Testing the API model.mp4 36.6 MB
3. Flask basics/3. Simple Flask API to add two numbers.mp4 36.4 MB
8. API for image recognition with deep learning/6. Generating test images.mp4 34.2 MB
4. Exposing a Random Forest Machine Learning service as an API/4. Pickling the Random Forest model.mp4 33.9 MB
3. Flask basics/4. Taking user input with GET requests.mp4 33.5 MB
8. API for image recognition with deep learning/5. Training and saving the trained deep learning model.mp4 31.0 MB
3. Flask basics/6. Using Flask in the context of Machine Learning.mp4 30.3 MB
5. Writing and building the Dockerfile/4. WORKDIR, RUN and CMD commands.mp4 29.5 MB
6. Building a production grade Docker application/1. Introduction.mp4 26.5 MB
6. Building a production grade Docker application/2. Overall Architecture.mp4 23.6 MB
5. Writing and building the Dockerfile/3. COPY and EXPOSE commands.mp4 21.7 MB
5. Writing and building the Dockerfile/5. Preparing the flask scripts for dockerizing.mp4 21.6 MB
2. Docker basics/1. Why docker.mp4 20.4 MB
8. API for image recognition with deep learning/8. Summary.mp4 18.4 MB
7. Building NLP based Text Clustering application/1. Introduction.mp4 18.1 MB
7. Building NLP based Text Clustering application/9. Summary.mp4 16.5 MB
2. Docker basics/3. Importance of docker containers in machine learning.mp4 14.8 MB
5. Writing and building the Dockerfile/2. Base Image & FROM command.mp4 14.8 MB
4. Exposing a Random Forest Machine Learning service as an API/9. Summary.mp4 13.5 MB
2. Docker basics/2. What are docker containers.mp4 12.1 MB
2. Docker basics/4. Where devops meets data science.mp4 11.6 MB
1. Course Overview/1. Introduction.mp4 10.5 MB
3. Flask basics/2. Setting up a Flask Project.mp4 9.2 MB
4. Exposing a Random Forest Machine Learning service as an API/2. API & Dataset Overview.mp4 7.6 MB
1. Course Overview/3. Skills Checklist.mp4 7.4 MB
1. Course Overview/2. I have a model. Now what.mp4 6.1 MB
8. API for image recognition with deep learning/1. Introduction.mp4 5.1 MB
1. Course Overview/4. Learning Goals.mp4 4.3 MB
3. Flask basics/1. Introduction.mp4 4.1 MB
4. Exposing a Random Forest Machine Learning service as an API/1. Introduction.mp4 3.9 MB
5. Writing and building the Dockerfile/1. Introduction.mp4 2.2 MB
2. Docker basics/5. Summary.mp4 2.1 MB
1. Course Overview/1.1 Course Overview.pdf.pdf 940.5 KB
2. Docker basics/1.1 Docker basics.pdf.pdf 833.5 KB
7. Building NLP based Text Clustering application/3. Converting unstructured to structured data.mp4.jpg 77.4 KB
2. Docker basics/2. What are docker containers.mp4.jpg 70.0 KB
6. Building a production grade Docker application/3.1 Docker deployment.zip.zip 11.5 KB
8. API for image recognition with deep learning/4. Building the deep learning model.vtt 10.1 KB
6. Building a production grade Docker application/5. Running and debugging a docker container in production.vtt 10.0 KB
7. Building NLP based Text Clustering application/2. Stemming & Lemmatization for cleaner text.vtt 9.9 KB
7. Building NLP based Text Clustering application/5. Preparing the excel output.vtt 9.7 KB
7. Building NLP based Text Clustering application/3. Converting unstructured to structured data.vtt 8.9 KB
5. Writing and building the Dockerfile/2.1 Docker sample.zip.zip 8.9 KB
4. Exposing a Random Forest Machine Learning service as an API/8. Flasgger for autogenerating UI.vtt 8.2 KB
5. Writing and building the Dockerfile/8. Running the Random Forest model on Docker.vtt 8.1 KB
5. Writing and building the Dockerfile/6. Writing the Dockerfile.vtt 8.1 KB
5. Writing and building the Dockerfile/7. Building the docker image.vtt 7.8 KB
8. API for image recognition with deep learning/3. Preparing the input images.vtt 7.6 KB
6. Building a production grade Docker application/3. Configuring the WSGI file.vtt 7.4 KB
7. Building NLP based Text Clustering application/4. KMeans Clustering.vtt 7.0 KB
6. Building a production grade Docker application/4. Writing a production grade Dockerfile.vtt 6.9 KB
8. API for image recognition with deep learning/7. Flask API wrapper for making predictions.vtt 6.3 KB
8. API for image recognition with deep learning/2. Visualizing the input images.vtt 6.3 KB
4. Exposing a Random Forest Machine Learning service as an API/7. Providing file input to Flask API.vtt 5.7 KB
7. Building NLP based Text Clustering application/8. Final output with charts.vtt 5.6 KB
7. Building NLP based Text Clustering application/7. Finding top keywords for kmeans clusters.vtt 5.5 KB
7. Building NLP based Text Clustering application/6. Making the output Downloadable.vtt 5.1 KB
3. Flask basics/5. POST request with Flask.vtt 5.1 KB
6. Building a production grade Docker application/2. Overall Architecture.vtt 4.3 KB
6. Building a production grade Docker application/1. Introduction.vtt 4.3 KB
4. Exposing a Random Forest Machine Learning service as an API/5. Exposing the Random Forest model as a Flask API.vtt 4.3 KB
4. Exposing a Random Forest Machine Learning service as an API/3. Training the Random Forest model.vtt 4.3 KB
5. Writing and building the Dockerfile/4. WORKDIR, RUN and CMD commands.vtt 3.8 KB
7. Building NLP based Text Clustering application/2.1 text_cluster_api.py.py 3.6 KB
4. Exposing a Random Forest Machine Learning service as an API/6. Testing the API model.vtt 3.5 KB
3. Flask basics/4. Taking user input with GET requests.vtt 3.4 KB
5. Writing and building the Dockerfile/3. COPY and EXPOSE commands.vtt 3.4 KB
3. Flask basics/3. Simple Flask API to add two numbers.vtt 3.4 KB
5. Writing and building the Dockerfile/2. Base Image & FROM command.vtt 3.2 KB
8. API for image recognition with deep learning/6. Generating test images.vtt 3.1 KB
2. Docker basics/3. Importance of docker containers in machine learning.vtt 3.0 KB
3. Flask basics/6. Using Flask in the context of Machine Learning.vtt 3.0 KB
8. API for image recognition with deep learning/5. Training and saving the trained deep learning model.vtt 2.9 KB
4. Exposing a Random Forest Machine Learning service as an API/4. Pickling the Random Forest model.vtt 2.4 KB
2. Docker basics/2. What are docker containers.vtt 2.3 KB
8. API for image recognition with deep learning/8. Summary.vtt 2.2 KB
7. Building NLP based Text Clustering application/1. Introduction.vtt 2.0 KB
8. API for image recognition with deep learning/2.1 img_reco_train.py.py 2.0 KB
4. Exposing a Random Forest Machine Learning service as an API/9. Summary.vtt 1.8 KB
1. Course Overview/3. Skills Checklist.vtt 1.8 KB
2. Docker basics/1. Why docker.vtt 1.7 KB
5. Writing and building the Dockerfile/5. Preparing the flask scripts for dockerizing.vtt 1.7 KB
4. Exposing a Random Forest Machine Learning service as an API/5.1 flask_predict_api.py.py 1.6 KB
7. Building NLP based Text Clustering application/9. Summary.vtt 1.6 KB
3. Flask basics/2. Setting up a Flask Project.vtt 1.5 KB
1. Course Overview/2. I have a model. Now what.vtt 1.3 KB
1. Course Overview/1. Introduction.vtt 1.1 KB
8. API for image recognition with deep learning/6.1 img_reco_test.py.py 1.0 KB
4. Exposing a Random Forest Machine Learning service as an API/2. API & Dataset Overview.vtt 1.0 KB
4. Exposing a Random Forest Machine Learning service as an API/2.1 flask_predict_train.py.py 1008 bytes
2. Docker basics/4. Where devops meets data science.vtt 987 bytes
8. API for image recognition with deep learning/1. Introduction.vtt 773 bytes
5. Writing and building the Dockerfile/1. Introduction.vtt 753 bytes
1. Course Overview/4. Learning Goals.vtt 708 bytes
4. Exposing a Random Forest Machine Learning service as an API/1. Introduction.vtt 678 bytes
3. Flask basics/1. Introduction.vtt 625 bytes
1. Course Overview/Must Read.txt 540 bytes
3. Flask basics/2.1 flask1.py.py 428 bytes
2. Docker basics/5. Summary.vtt 382 bytes
7. Building NLP based Text Clustering application/3. Converting unstructured to structured data.txt 244 bytes
2. Docker basics/2. What are docker containers.txt 226 bytes
7. Building NLP based Text Clustering application/10. Dockerizing the text clustering app.html 164 bytes
8. API for image recognition with deep learning/9. Dockerizing the deep learning app.html 164 bytes
6. Building a production grade Docker application/6. Docker Quiz 1 – Basic Concepts, Commands.html 160 bytes
1. Course Overview/Visit Coursedrive.org.url 124 bytes
[DesireCourse.Net].url 51 bytes
[CourseClub.Me].url 48 bytes

[DesireCourse.Net] Udemy - Deploy Machine Learning & NLP Models with Dockers (DevOps)

File List

Download Torrent

Related Resources

Copyright Infringement