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[DesireCourse.Net] Udemy - Deploy Machine Learning & NLP Models with Dockers (DevOps)
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文档列表
7. Building NLP based Text Clustering application/5. Preparing the excel output.mp4
114.1 MB
7. Building NLP based Text Clustering application/3. Converting unstructured to structured data.mp4
100.3 MB
8. API for image recognition with deep learning/4. Building the deep learning model.mp4
97.7 MB
7. Building NLP based Text Clustering application/2. Stemming & Lemmatization for cleaner text.mp4
95.3 MB
8. API for image recognition with deep learning/3. Preparing the input images.mp4
93.9 MB
6. Building a production grade Docker application/5. Running and debugging a docker container in production.mp4
90.2 MB
4. Exposing a Random Forest Machine Learning service as an API/8. Flasgger for autogenerating UI.mp4
89.3 MB
7. Building NLP based Text Clustering application/4. KMeans Clustering.mp4
86.2 MB
5. Writing and building the Dockerfile/8. Running the Random Forest model on Docker.mp4
82.6 MB
8. API for image recognition with deep learning/7. Flask API wrapper for making predictions.mp4
82.1 MB
7. Building NLP based Text Clustering application/8. Final output with charts.mp4
80.1 MB
4. Exposing a Random Forest Machine Learning service as an API/7. Providing file input to Flask API.mp4
79.4 MB
7. Building NLP based Text Clustering application/7. Finding top keywords for kmeans clusters.mp4
78.6 MB
5. Writing and building the Dockerfile/7. Building the docker image.mp4
78.4 MB
8. API for image recognition with deep learning/2. Visualizing the input images.mp4
71.7 MB
7. Building NLP based Text Clustering application/6. Making the output Downloadable.mp4
68.7 MB
6. Building a production grade Docker application/3. Configuring the WSGI file.mp4
65.5 MB
6. Building a production grade Docker application/4. Writing a production grade Dockerfile.mp4
64.4 MB
4. Exposing a Random Forest Machine Learning service as an API/5. Exposing the Random Forest model as a Flask API.mp4
56.9 MB
3. Flask basics/5. POST request with Flask.mp4
50.3 MB
5. Writing and building the Dockerfile/6. Writing the Dockerfile.mp4
48.2 MB
4. Exposing a Random Forest Machine Learning service as an API/3. Training the Random Forest model.mp4
48.0 MB
4. Exposing a Random Forest Machine Learning service as an API/6. Testing the API model.mp4
38.4 MB
3. Flask basics/3. Simple Flask API to add two numbers.mp4
38.2 MB
8. API for image recognition with deep learning/6. Generating test images.mp4
35.9 MB
4. Exposing a Random Forest Machine Learning service as an API/4. Pickling the Random Forest model.mp4
35.5 MB
3. Flask basics/4. Taking user input with GET requests.mp4
35.1 MB
8. API for image recognition with deep learning/5. Training and saving the trained deep learning model.mp4
32.5 MB
3. Flask basics/6. Using Flask in the context of Machine Learning.mp4
31.7 MB
5. Writing and building the Dockerfile/4. WORKDIR, RUN and CMD commands.mp4
31.0 MB
6. Building a production grade Docker application/1. Introduction.mp4
27.8 MB
6. Building a production grade Docker application/2. Overall Architecture.mp4
24.8 MB
5. Writing and building the Dockerfile/3. COPY and EXPOSE commands.mp4
22.8 MB
5. Writing and building the Dockerfile/5. Preparing the flask scripts for dockerizing.mp4
22.6 MB
2. Docker basics/1. Why docker.mp4
21.4 MB
8. API for image recognition with deep learning/8. Summary.mp4
19.3 MB
7. Building NLP based Text Clustering application/1. Introduction.mp4
19.0 MB
7. Building NLP based Text Clustering application/9. Summary.mp4
17.3 MB
2. Docker basics/3. Importance of docker containers in machine learning.mp4
15.5 MB
5. Writing and building the Dockerfile/2. Base Image & FROM command.mp4
15.5 MB
4. Exposing a Random Forest Machine Learning service as an API/9. Summary.mp4
14.2 MB
2. Docker basics/2. What are docker containers.mp4
12.6 MB
2. Docker basics/4. Where devops meets data science.mp4
12.2 MB
1. Course Overview/1. Introduction.mp4
11.0 MB
3. Flask basics/2. Setting up a Flask Project.mp4
9.6 MB
4. Exposing a Random Forest Machine Learning service as an API/2. API & Dataset Overview.mp4
8.0 MB
1. Course Overview/3. Skills Checklist.mp4
7.8 MB
1. Course Overview/2. I have a model. Now what.mp4
6.4 MB
8. API for image recognition with deep learning/1. Introduction.mp4
5.3 MB
1. Course Overview/4. Learning Goals.mp4
4.5 MB
3. Flask basics/1. Introduction.mp4
4.3 MB
4. Exposing a Random Forest Machine Learning service as an API/1. Introduction.mp4
4.1 MB
5. Writing and building the Dockerfile/1. Introduction.mp4
2.3 MB
2. Docker basics/5. Summary.mp4
2.2 MB
1. Course Overview/1.1 Course Overview.pdf.pdf
963.0 kB
2. Docker basics/1.1 Docker basics.pdf.pdf
853.5 kB
7. Building NLP based Text Clustering application/3. Converting unstructured to structured data.mp4.jpg
79.3 kB
2. Docker basics/2. What are docker containers.mp4.jpg
71.7 kB
6. Building a production grade Docker application/3.1 Docker deployment.zip.zip
11.8 kB
8. API for image recognition with deep learning/4. Building the deep learning model.vtt
10.3 kB
6. Building a production grade Docker application/5. Running and debugging a docker container in production.vtt
10.3 kB
7. Building NLP based Text Clustering application/2. Stemming & Lemmatization for cleaner text.vtt
10.1 kB
7. Building NLP based Text Clustering application/5. Preparing the excel output.vtt
9.9 kB
7. Building NLP based Text Clustering application/3. Converting unstructured to structured data.vtt
9.1 kB
5. Writing and building the Dockerfile/2.1 Docker sample.zip.zip
9.1 kB
4. Exposing a Random Forest Machine Learning service as an API/8. Flasgger for autogenerating UI.vtt
8.4 kB
5. Writing and building the Dockerfile/8. Running the Random Forest model on Docker.vtt
8.3 kB
5. Writing and building the Dockerfile/6. Writing the Dockerfile.vtt
8.3 kB
5. Writing and building the Dockerfile/7. Building the docker image.vtt
7.9 kB
8. API for image recognition with deep learning/3. Preparing the input images.vtt
7.8 kB
6. Building a production grade Docker application/3. Configuring the WSGI file.vtt
7.6 kB
7. Building NLP based Text Clustering application/4. KMeans Clustering.vtt
7.2 kB
6. Building a production grade Docker application/4. Writing a production grade Dockerfile.vtt
7.1 kB
8. API for image recognition with deep learning/7. Flask API wrapper for making predictions.vtt
6.5 kB
8. API for image recognition with deep learning/2. Visualizing the input images.vtt
6.4 kB
4. Exposing a Random Forest Machine Learning service as an API/7. Providing file input to Flask API.vtt
5.8 kB
7. Building NLP based Text Clustering application/8. Final output with charts.vtt
5.7 kB
7. Building NLP based Text Clustering application/7. Finding top keywords for kmeans clusters.vtt
5.7 kB
7. Building NLP based Text Clustering application/6. Making the output Downloadable.vtt
5.2 kB
3. Flask basics/5. POST request with Flask.vtt
5.2 kB
6. Building a production grade Docker application/2. Overall Architecture.vtt
4.4 kB
6. Building a production grade Docker application/1. Introduction.vtt
4.4 kB
4. Exposing a Random Forest Machine Learning service as an API/5. Exposing the Random Forest model as a Flask API.vtt
4.4 kB
4. Exposing a Random Forest Machine Learning service as an API/3. Training the Random Forest model.vtt
4.4 kB
5. Writing and building the Dockerfile/4. WORKDIR, RUN and CMD commands.vtt
3.9 kB
7. Building NLP based Text Clustering application/2.1 text_cluster_api.py.py
3.7 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
3.5 kB
5. Writing and building the Dockerfile/3. COPY and EXPOSE commands.vtt
3.5 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
3.3 kB
8. API for image recognition with deep learning/6. Generating test images.vtt
3.2 kB
2. Docker basics/3. Importance of docker containers in machine learning.vtt
3.1 kB
3. Flask basics/6. Using Flask in the context of Machine Learning.vtt
3.1 kB
8. API for image recognition with deep learning/5. Training and saving the trained deep learning model.vtt
3.0 kB
4. Exposing a Random Forest Machine Learning service as an API/4. Pickling the Random Forest model.vtt
2.5 kB
2. Docker basics/2. What are docker containers.vtt
2.3 kB
8. API for image recognition with deep learning/8. Summary.vtt
2.3 kB
7. Building NLP based Text Clustering application/1. Introduction.vtt
2.1 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
1.9 kB
1. Course Overview/3. Skills Checklist.vtt
1.8 kB
2. Docker basics/1. Why docker.vtt
1.8 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
1.7 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
1.1 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
1.0 kB
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
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