Linkedin - Full-Stack Deep Learning with Python --> [ FreeCourseWeb ]

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Torrent File Content (59 files)

[ FreeCourseWeb.com ] Linkedin - Full-Stack Deep Learning with Python
Get Bonus Downloads Here.url -

183 bytes

~Get Your Files Here !
01 - Introduction/01 - Full-stack deep learning, MLOps, and MLflow.mp4 -

9.8 MB

01 - Introduction/01 - Full-stack deep learning, MLOps, and MLflow.srt -

12.53 KB

01 - Introduction/02 - Prerequisites.mp4 -

898.79 KB

01 - Introduction/02 - Prerequisites.srt -

1.11 KB

02 - 1. An Overview of Full-Stack Deep Learning/01 - Introducing full-stack deep learning.mp4 -

7.78 MB

02 - 1. An Overview of Full-Stack Deep Learning/01 - Introducing full-stack deep learning.srt -

11.36 KB

02 - 1. An Overview of Full-Stack Deep Learning/02 - Introducing MLOps.mp4 -

6.62 MB

02 - 1. An Overview of Full-Stack Deep Learning/02 - Introducing MLOps.srt -

7.58 KB

02 - 1. An Overview of Full-Stack Deep Learning/03 - Introducing MLflow.mp4 -

6.32 MB

02 - 1. An Overview of Full-Stack Deep Learning/03 - Introducing MLflow.srt -

7.86 KB

02 - 1. An Overview of Full-Stack Deep Learning/04 - Setting up the environment on Google Colab.mp4 -

13.02 MB

02 - 1. An Overview of Full-Stack Deep Learning/04 - Setting up the environment on Google Colab.srt -

9.16 KB

02 - 1. An Overview of Full-Stack Deep Learning/05 - Running MLflow and using ngrok to access the MLflow UI.mp4 -

10.26 MB

02 - 1. An Overview of Full-Stack Deep Learning/05 - Running MLflow and using ngrok to access the MLflow UI.srt -

9.74 KB

03 - 2. Model Training and Evaluation Using MLflow/01 - Loading and exploring the EMNIST dataset.mp4 -

9.94 MB

03 - 2. Model Training and Evaluation Using MLflow/01 - Loading and exploring the EMNIST dataset.srt -

8.8 KB

03 - 2. Model Training and Evaluation Using MLflow/02 - Logging metrics, parameters, and artifacts in MLflow.mp4 -

11.05 MB

03 - 2. Model Training and Evaluation Using MLflow/02 - Logging metrics, parameters, and artifacts in MLflow.srt -

10.95 KB

03 - 2. Model Training and Evaluation Using MLflow/03 - Set up the dataset and data loader.mp4 -

6.9 MB

03 - 2. Model Training and Evaluation Using MLflow/03 - Set up the dataset and data loader.srt -

6.44 KB

03 - 2. Model Training and Evaluation Using MLflow/04 - Configuring the image classification DNN model.mp4 -

10.48 MB

03 - 2. Model Training and Evaluation Using MLflow/04 - Configuring the image classification DNN model.srt -

8.71 KB

03 - 2. Model Training and Evaluation Using MLflow/05 - Training a model within an MLflow run.mp4 -

11.14 MB

03 - 2. Model Training and Evaluation Using MLflow/05 - Training a model within an MLflow run.srt -

7.04 KB

03 - 2. Model Training and Evaluation Using MLflow/06 - Exploring parameters and metrics in MLflow.mp4 -

9.04 MB

03 - 2. Model Training and Evaluation Using MLflow/06 - Exploring parameters and metrics in MLflow.srt -

7.94 KB

03 - 2. Model Training and Evaluation Using MLflow/07 - Making predictions using MLflow artifacts.mp4 -

11.35 MB

03 - 2. Model Training and Evaluation Using MLflow/07 - Making predictions using MLflow artifacts.srt -

8.82 KB

04 - 3. Model Training and Hyperparameter Tuning/01 - Preparing data for image classification using CNN.mp4 -

9.74 MB

04 - 3. Model Training and Hyperparameter Tuning/01 - Preparing data for image classification using CNN.srt -

6.93 KB

04 - 3. Model Training and Hyperparameter Tuning/02 - Configuring and training the model using MLflow runs.mp4 -

15.5 MB

04 - 3. Model Training and Hyperparameter Tuning/02 - Configuring and training the model using MLflow runs.srt -

10.85 KB

04 - 3. Model Training and Hyperparameter Tuning/03 - Visualizing charts, metrics, and parameters on MLflow.mp4 -

15.23 MB

04 - 3. Model Training and Hyperparameter Tuning/03 - Visualizing charts, metrics, and parameters on MLflow.srt -

11.96 KB

04 - 3. Model Training and Hyperparameter Tuning/04 - Setting up the objective function for hyperparameter tuning.mp4 -

12.36 MB

04 - 3. Model Training and Hyperparameter Tuning/04 - Setting up the objective function for hyperparameter tuning.srt -

9.82 KB

04 - 3. Model Training and Hyperparameter Tuning/05 - Hyperparameter optimization with Hyperopt and MLflow.mp4 -

13.88 MB

04 - 3. Model Training and Hyperparameter Tuning/05 - Hyperparameter optimization with Hyperopt and MLflow.srt -

11.65 KB

04 - 3. Model Training and Hyperparameter Tuning/06 - Identifying the best model.mp4 -

7.79 MB

04 - 3. Model Training and Hyperparameter Tuning/06 - Identifying the best model.srt -

5.96 KB

04 - 3. Model Training and Hyperparameter Tuning/07 - Registering a model with the MLflow registry.mp4 -

5.68 MB

04 - 3. Model Training and Hyperparameter Tuning/07 - Registering a model with the MLflow registry.srt -

6.05 KB

05 - 4. Model Deployment and Predictions/01 - Setting up MLflow on the local machine.mp4 -

8.18 MB

05 - 4. Model Deployment and Predictions/01 - Setting up MLflow on the local machine.srt -

8.42 KB

05 - 4. Model Deployment and Predictions/02 - Workaround to get model artifacts on the local machine.mp4 -

4.27 MB

05 - 4. Model Deployment and Predictions/02 - Workaround to get model artifacts on the local machine.srt -

3.88 KB

05 - 4. Model Deployment and Predictions/03 - Deploying and serving the model locally.mp4 -

13.76 MB

05 - 4. Model Deployment and Predictions/03 - Deploying and serving the model locally.srt -

10.63 KB

06 - Conclusion/01 - Summary and next steps.mp4 -

2.47 MB

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