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

  • 收录时间:2020-12-29 02:18:17
  • 文件大小:2GB
  • 下载次数:4
  • 最近下载:2021-01-03 16:43:02
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文件列表

  1. 7. Building NLP based Text Clustering application/5. Preparing the excel output.mp4 109MB
  2. 7. Building NLP based Text Clustering application/3. Converting unstructured to structured data.mp4 96MB
  3. 8. API for image recognition with deep learning/4. Building the deep learning model.mp4 93MB
  4. 7. Building NLP based Text Clustering application/2. Stemming & Lemmatization for cleaner text.mp4 91MB
  5. 8. API for image recognition with deep learning/3. Preparing the input images.mp4 90MB
  6. 6. Building a production grade Docker application/5. Running and debugging a docker container in production.mp4 86MB
  7. 4. Exposing a Random Forest Machine Learning service as an API/8. Flasgger for autogenerating UI.mp4 85MB
  8. 7. Building NLP based Text Clustering application/4. KMeans Clustering.mp4 82MB
  9. 5. Writing and building the Dockerfile/8. Running the Random Forest model on Docker.mp4 79MB
  10. 8. API for image recognition with deep learning/7. Flask API wrapper for making predictions.mp4 78MB
  11. 7. Building NLP based Text Clustering application/8. Final output with charts.mp4 76MB
  12. 4. Exposing a Random Forest Machine Learning service as an API/7. Providing file input to Flask API.mp4 76MB
  13. 7. Building NLP based Text Clustering application/7. Finding top keywords for kmeans clusters.mp4 75MB
  14. 5. Writing and building the Dockerfile/7. Building the docker image.mp4 75MB
  15. 8. API for image recognition with deep learning/2. Visualizing the input images.mp4 68MB
  16. 7. Building NLP based Text Clustering application/6. Making the output Downloadable.mp4 66MB
  17. 6. Building a production grade Docker application/3. Configuring the WSGI file.mp4 62MB
  18. 6. Building a production grade Docker application/4. Writing a production grade Dockerfile.mp4 61MB
  19. 4. Exposing a Random Forest Machine Learning service as an API/5. Exposing the Random Forest model as a Flask API.mp4 54MB
  20. 3. Flask basics/5. POST request with Flask.mp4 48MB
  21. 5. Writing and building the Dockerfile/6. Writing the Dockerfile.mp4 46MB
  22. 4. Exposing a Random Forest Machine Learning service as an API/3. Training the Random Forest model.mp4 46MB
  23. 4. Exposing a Random Forest Machine Learning service as an API/6. Testing the API model.mp4 37MB
  24. 3. Flask basics/3. Simple Flask API to add two numbers.mp4 36MB
  25. 8. API for image recognition with deep learning/6. Generating test images.mp4 34MB
  26. 4. Exposing a Random Forest Machine Learning service as an API/4. Pickling the Random Forest model.mp4 34MB
  27. 3. Flask basics/4. Taking user input with GET requests.mp4 33MB
  28. 8. API for image recognition with deep learning/5. Training and saving the trained deep learning model.mp4 31MB
  29. 3. Flask basics/6. Using Flask in the context of Machine Learning.mp4 30MB
  30. 5. Writing and building the Dockerfile/4. WORKDIR, RUN and CMD commands.mp4 30MB
  31. 6. Building a production grade Docker application/1. Introduction.mp4 27MB
  32. 6. Building a production grade Docker application/2. Overall Architecture.mp4 24MB
  33. 5. Writing and building the Dockerfile/3. COPY and EXPOSE commands.mp4 22MB
  34. 5. Writing and building the Dockerfile/5. Preparing the flask scripts for dockerizing.mp4 22MB
  35. 2. Docker basics/1. Why docker.mp4 20MB
  36. 8. API for image recognition with deep learning/8. Summary.mp4 18MB
  37. 7. Building NLP based Text Clustering application/1. Introduction.mp4 18MB
  38. 7. Building NLP based Text Clustering application/9. Summary.mp4 16MB
  39. 2. Docker basics/3. Importance of docker containers in machine learning.mp4 15MB
  40. 5. Writing and building the Dockerfile/2. Base Image & FROM command.mp4 15MB
  41. 4. Exposing a Random Forest Machine Learning service as an API/9. Summary.mp4 13MB
  42. 2. Docker basics/2. What are docker containers.mp4 12MB
  43. 2. Docker basics/4. Where devops meets data science.mp4 12MB
  44. 1. Course Overview/1. Introduction.mp4 10MB
  45. 3. Flask basics/2. Setting up a Flask Project.mp4 9MB
  46. 4. Exposing a Random Forest Machine Learning service as an API/2. API & Dataset Overview.mp4 8MB
  47. 1. Course Overview/3. Skills Checklist.mp4 7MB
  48. 1. Course Overview/2. I have a model. Now what.mp4 6MB
  49. 8. API for image recognition with deep learning/1. Introduction.mp4 5MB
  50. 1. Course Overview/4. Learning Goals.mp4 4MB
  51. 3. Flask basics/1. Introduction.mp4 4MB
  52. 4. Exposing a Random Forest Machine Learning service as an API/1. Introduction.mp4 4MB
  53. 5. Writing and building the Dockerfile/1. Introduction.mp4 2MB
  54. 2. Docker basics/5. Summary.mp4 2MB
  55. 1. Course Overview/1.1 Course Overview.pdf.pdf 940KB
  56. 2. Docker basics/1.1 Docker basics.pdf.pdf 834KB
  57. 7. Building NLP based Text Clustering application/3. Converting unstructured to structured data.mp4.jpg 77KB
  58. 2. Docker basics/2. What are docker containers.mp4.jpg 70KB
  59. 6. Building a production grade Docker application/3.1 Docker deployment.zip.zip 12KB
  60. 8. API for image recognition with deep learning/4. Building the deep learning model.vtt 10KB
  61. 6. Building a production grade Docker application/5. Running and debugging a docker container in production.vtt 10KB
  62. 7. Building NLP based Text Clustering application/2. Stemming & Lemmatization for cleaner text.vtt 10KB
  63. 7. Building NLP based Text Clustering application/5. Preparing the excel output.vtt 10KB
  64. 7. Building NLP based Text Clustering application/3. Converting unstructured to structured data.vtt 9KB
  65. 5. Writing and building the Dockerfile/2.1 Docker sample.zip.zip 9KB
  66. 4. Exposing a Random Forest Machine Learning service as an API/8. Flasgger for autogenerating UI.vtt 8KB
  67. 5. Writing and building the Dockerfile/8. Running the Random Forest model on Docker.vtt 8KB
  68. 5. Writing and building the Dockerfile/6. Writing the Dockerfile.vtt 8KB
  69. 5. Writing and building the Dockerfile/7. Building the docker image.vtt 8KB
  70. 8. API for image recognition with deep learning/3. Preparing the input images.vtt 8KB
  71. 6. Building a production grade Docker application/3. Configuring the WSGI file.vtt 7KB
  72. 7. Building NLP based Text Clustering application/4. KMeans Clustering.vtt 7KB
  73. 6. Building a production grade Docker application/4. Writing a production grade Dockerfile.vtt 7KB
  74. 8. API for image recognition with deep learning/7. Flask API wrapper for making predictions.vtt 6KB
  75. 8. API for image recognition with deep learning/2. Visualizing the input images.vtt 6KB
  76. 4. Exposing a Random Forest Machine Learning service as an API/7. Providing file input to Flask API.vtt 6KB
  77. 7. Building NLP based Text Clustering application/8. Final output with charts.vtt 6KB
  78. 7. Building NLP based Text Clustering application/7. Finding top keywords for kmeans clusters.vtt 6KB
  79. 7. Building NLP based Text Clustering application/6. Making the output Downloadable.vtt 5KB
  80. 3. Flask basics/5. POST request with Flask.vtt 5KB
  81. 6. Building a production grade Docker application/2. Overall Architecture.vtt 4KB
  82. 6. Building a production grade Docker application/1. Introduction.vtt 4KB
  83. 4. Exposing a Random Forest Machine Learning service as an API/5. Exposing the Random Forest model as a Flask API.vtt 4KB
  84. 4. Exposing a Random Forest Machine Learning service as an API/3. Training the Random Forest model.vtt 4KB
  85. 5. Writing and building the Dockerfile/4. WORKDIR, RUN and CMD commands.vtt 4KB
  86. 7. Building NLP based Text Clustering application/2.1 text_cluster_api.py.py 4KB
  87. 4. Exposing a Random Forest Machine Learning service as an API/6. Testing the API model.vtt 3KB
  88. 3. Flask basics/4. Taking user input with GET requests.vtt 3KB
  89. 5. Writing and building the Dockerfile/3. COPY and EXPOSE commands.vtt 3KB
  90. 3. Flask basics/3. Simple Flask API to add two numbers.vtt 3KB
  91. 5. Writing and building the Dockerfile/2. Base Image & FROM command.vtt 3KB
  92. 8. API for image recognition with deep learning/6. Generating test images.vtt 3KB
  93. 2. Docker basics/3. Importance of docker containers in machine learning.vtt 3KB
  94. 3. Flask basics/6. Using Flask in the context of Machine Learning.vtt 3KB
  95. 8. API for image recognition with deep learning/5. Training and saving the trained deep learning model.vtt 3KB
  96. 4. Exposing a Random Forest Machine Learning service as an API/4. Pickling the Random Forest model.vtt 2KB
  97. 2. Docker basics/2. What are docker containers.vtt 2KB
  98. 8. API for image recognition with deep learning/8. Summary.vtt 2KB
  99. 7. Building NLP based Text Clustering application/1. Introduction.vtt 2KB
  100. 8. API for image recognition with deep learning/2.1 img_reco_train.py.py 2KB
  101. 4. Exposing a Random Forest Machine Learning service as an API/9. Summary.vtt 2KB
  102. 1. Course Overview/3. Skills Checklist.vtt 2KB
  103. 2. Docker basics/1. Why docker.vtt 2KB
  104. 5. Writing and building the Dockerfile/5. Preparing the flask scripts for dockerizing.vtt 2KB
  105. 4. Exposing a Random Forest Machine Learning service as an API/5.1 flask_predict_api.py.py 2KB
  106. 7. Building NLP based Text Clustering application/9. Summary.vtt 2KB
  107. 3. Flask basics/2. Setting up a Flask Project.vtt 1KB
  108. 1. Course Overview/2. I have a model. Now what.vtt 1KB
  109. 1. Course Overview/1. Introduction.vtt 1KB
  110. 8. API for image recognition with deep learning/6.1 img_reco_test.py.py 1KB
  111. 4. Exposing a Random Forest Machine Learning service as an API/2. API & Dataset Overview.vtt 1KB
  112. 4. Exposing a Random Forest Machine Learning service as an API/2.1 flask_predict_train.py.py 1008B
  113. 2. Docker basics/4. Where devops meets data science.vtt 987B
  114. 8. API for image recognition with deep learning/1. Introduction.vtt 773B
  115. 5. Writing and building the Dockerfile/1. Introduction.vtt 753B
  116. 1. Course Overview/4. Learning Goals.vtt 708B
  117. 4. Exposing a Random Forest Machine Learning service as an API/1. Introduction.vtt 678B
  118. 3. Flask basics/1. Introduction.vtt 625B
  119. 1. Course Overview/Must Read.txt 540B
  120. 3. Flask basics/2.1 flask1.py.py 428B
  121. 2. Docker basics/5. Summary.vtt 382B
  122. 7. Building NLP based Text Clustering application/3. Converting unstructured to structured data.txt 244B
  123. 2. Docker basics/2. What are docker containers.txt 226B
  124. 7. Building NLP based Text Clustering application/10. Dockerizing the text clustering app.html 164B
  125. 8. API for image recognition with deep learning/9. Dockerizing the deep learning app.html 164B
  126. 6. Building a production grade Docker application/6. Docker Quiz 1 – Basic Concepts, Commands.html 160B
  127. 1. Course Overview/Visit Coursedrive.org.url 124B
  128. [DesireCourse.Net].url 51B
  129. [CourseClub.Me].url 48B