[ FreeCourseWeb.com ] Linkedin - Full-Stack Deep Learning with Python

磁力链接/BT种子名称

[ FreeCourseWeb.com ] Linkedin - Full-Stack Deep Learning with Python

磁力链接/BT种子简介

种子哈希：d9fcdbd577a3e325e97e35c113aa74ad0c683f7f
文件大小：431.12M
已经下载：5208次
下载速度：极快
收录时间：2024-02-20
最近下载：2025-05-30

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文件列表

  • ~Get Your Files Here !/Ex_Files_Full_Stack_Deep_Learning_Python/Exercise Files/final_code/datasets/emnist-letters-train.csv 171.6 MB
  • ~Get Your Files Here !/Ex_Files_Full_Stack_Deep_Learning_Python/Exercise Files/final_code/datasets/emnist-letters-test.csv 28.6 MB
  • ~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/02 - Configuring and training the model using MLflow runs.mp4 16.3 MB
  • ~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/03 - Visualizing charts, metrics, and parameters on MLflow.mp4 16.0 MB
  • ~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/05 - Hyperparameter optimization with Hyperopt and MLflow.mp4 14.6 MB
  • ~Get Your Files Here !/05 - 4. Model Deployment and Predictions/03 - Deploying and serving the model locally.mp4 14.4 MB
  • ~Get Your Files Here !/02 - 1. An Overview of Full-Stack Deep Learning/04 - Setting up the environment on Google Colab.mp4 13.7 MB
  • ~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/04 - Setting up the objective function for hyperparameter tuning.mp4 13.0 MB
  • ~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/07 - Making predictions using MLflow artifacts.mp4 11.9 MB
  • ~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/05 - Training a model within an MLflow run.mp4 11.7 MB
  • ~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/02 - Logging metrics, parameters, and artifacts in MLflow.mp4 11.6 MB
  • ~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/04 - Configuring the image classification DNN model.mp4 11.0 MB
  • ~Get Your Files Here !/02 - 1. An Overview of Full-Stack Deep Learning/05 - Running MLflow and using ngrok to access the MLflow UI.mp4 10.8 MB
  • ~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/01 - Loading and exploring the EMNIST dataset.mp4 10.4 MB
  • ~Get Your Files Here !/01 - Introduction/01 - Full-stack deep learning, MLOps, and MLflow.mp4 10.3 MB
  • ~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/01 - Preparing data for image classification using CNN.mp4 10.2 MB
  • ~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/06 - Exploring parameters and metrics in MLflow.mp4 9.5 MB
  • ~Get Your Files Here !/05 - 4. Model Deployment and Predictions/01 - Setting up MLflow on the local machine.mp4 8.6 MB
  • ~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/06 - Identifying the best model.mp4 8.2 MB
  • ~Get Your Files Here !/02 - 1. An Overview of Full-Stack Deep Learning/01 - Introducing full-stack deep learning.mp4 8.2 MB
  • ~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/03 - Set up the dataset and data loader.mp4 7.2 MB
  • ~Get Your Files Here !/02 - 1. An Overview of Full-Stack Deep Learning/02 - Introducing MLOps.mp4 6.9 MB
  • ~Get Your Files Here !/02 - 1. An Overview of Full-Stack Deep Learning/03 - Introducing MLflow.mp4 6.6 MB
  • ~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/07 - Registering a model with the MLflow registry.mp4 6.0 MB
  • ~Get Your Files Here !/05 - 4. Model Deployment and Predictions/02 - Workaround to get model artifacts on the local machine.mp4 4.5 MB
  • ~Get Your Files Here !/Ex_Files_Full_Stack_Deep_Learning_Python/Exercise Files/final_code/demo_02_EMNISTClassificationUsingCNN.ipynb 3.3 MB
  • ~Get Your Files Here !/06 - Conclusion/01 - Summary and next steps.mp4 2.6 MB
  • ~Get Your Files Here !/Ex_Files_Full_Stack_Deep_Learning_Python/Exercise Files/final_code/demo_01_EMNISTClassificationUsingDNN.ipynb 1.7 MB
  • ~Get Your Files Here !/Ex_Files_Full_Stack_Deep_Learning_Python/Exercise Files/final_code/ipynb_checkpoints/demo_01_EMNISTClassificationUsingDNN-checkpoint.ipynb 1.7 MB
  • ~Get Your Files Here !/01 - Introduction/02 - Prerequisites.mp4 920.4 kB
  • ~Get Your Files Here !/Ex_Files_Full_Stack_Deep_Learning_Python/Exercise Files/final_code/ipynb_checkpoints/demo_03_ModelDeployment-checkpoint.ipynb 47.4 kB
  • ~Get Your Files Here !/Ex_Files_Full_Stack_Deep_Learning_Python/Exercise Files/final_code/demo_03_ModelDeployment.ipynb 38.6 kB
  • ~Get Your Files Here !/01 - Introduction/01 - Full-stack deep learning, MLOps, and MLflow.srt 12.8 kB
  • ~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/03 - Visualizing charts, metrics, and parameters on MLflow.srt 12.2 kB
  • ~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/05 - Hyperparameter optimization with Hyperopt and MLflow.srt 11.9 kB
  • ~Get Your Files Here !/02 - 1. An Overview of Full-Stack Deep Learning/01 - Introducing full-stack deep learning.srt 11.6 kB
  • ~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/02 - Logging metrics, parameters, and artifacts in MLflow.srt 11.2 kB
  • ~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/02 - Configuring and training the model using MLflow runs.srt 11.1 kB
  • ~Get Your Files Here !/05 - 4. Model Deployment and Predictions/03 - Deploying and serving the model locally.srt 10.9 kB
  • ~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/04 - Setting up the objective function for hyperparameter tuning.srt 10.1 kB
  • ~Get Your Files Here !/02 - 1. An Overview of Full-Stack Deep Learning/05 - Running MLflow and using ngrok to access the MLflow UI.srt 10.0 kB
  • ~Get Your Files Here !/02 - 1. An Overview of Full-Stack Deep Learning/04 - Setting up the environment on Google Colab.srt 9.4 kB
  • ~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/07 - Making predictions using MLflow artifacts.srt 9.0 kB
  • ~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/01 - Loading and exploring the EMNIST dataset.srt 9.0 kB
  • ~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/04 - Configuring the image classification DNN model.srt 8.9 kB
  • ~Get Your Files Here !/05 - 4. Model Deployment and Predictions/01 - Setting up MLflow on the local machine.srt 8.6 kB
  • ~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/06 - Exploring parameters and metrics in MLflow.srt 8.1 kB
  • ~Get Your Files Here !/02 - 1. An Overview of Full-Stack Deep Learning/03 - Introducing MLflow.srt 8.1 kB
  • ~Get Your Files Here !/02 - 1. An Overview of Full-Stack Deep Learning/02 - Introducing MLOps.srt 7.8 kB
  • ~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/05 - Training a model within an MLflow run.srt 7.2 kB
  • ~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/01 - Preparing data for image classification using CNN.srt 7.1 kB
  • ~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/03 - Set up the dataset and data loader.srt 6.6 kB
  • ~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/07 - Registering a model with the MLflow registry.srt 6.2 kB
  • ~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/06 - Identifying the best model.srt 6.1 kB
  • ~Get Your Files Here !/05 - 4. Model Deployment and Predictions/02 - Workaround to get model artifacts on the local machine.srt 4.0 kB
  • ~Get Your Files Here !/06 - Conclusion/01 - Summary and next steps.srt 3.3 kB
  • ~Get Your Files Here !/01 - Introduction/02 - Prerequisites.srt 1.1 kB
  • ~Get Your Files Here !/Bonus Resources.txt 386 Bytes
  • Get Bonus Downloads Here.url 183 Bytes

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本站不存储任何资源内容，只收集BT种子元数据(例如文件名和文件大小)和磁力链接(BT种子标识符)，并提供查询服务，是一个完全合法的搜索引擎系统。 网站不提供种子下载服务，用户可以通过第三方链接或磁力链接获取到相关的种子资源。本站也不对BT种子真实性及合法性负责，请用户注意甄别！
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