Linkedin - Full-Stack Deep Learning With Python

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Linkedin - Full-Stack Deep Learning with Python

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Linkedin - Full-Stack Deep Learning with Python.torrent
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d9fcdbd577a3e325e97e35c113aa74ad0c683f7f
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431 MB in 58 files
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Uploaded on 15-02-2024 by our crawler pet called "Spidey".
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Description

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



If You Need More Stuff, kindly Visit and Support Us -->> https://FreeCourseWeb.com







Released 2/2024

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch

Skill Level: Advanced | Genre: eLearning | Language: English + srt | Duration: 1h 58 | Size: 268 MB



If you seek a more in-depth understanding of deep learning and Python, this hands-on course can help you. In this course, certified Google cloud architect and data engineer Janani Ravi guides you through the intricacies of full-stack deep learning with Python. After a review of full stack deep learning, MLOps, and MLflow, dive into setting up your environment on Google Colab and running MLflow. Learn how to load and explore a dataset, as well as how to log metrics, parameters, and artifacts. Explore model training, evaluation, and hyperparameter tuning. Plus, go over model deployment and predictions.





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We upload these learning materials for the people from all over the world, who have the talent and motivation to sharpen their skills/ knowledge but do not have the financial support to afford the materials. If you like this content and if you are truly in a position that you can actually buy the materials, then Please, we repeat, Please, Support Authors. They Deserve it! Because always remember, without "Them", you and we won't be here having this conversation. Think about it! Peace...



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Files in this torrent

FILENAMESIZE
~Get Your Files Here !/01 - Introduction/01 - Full-stack deep learning, MLOps, and MLflow.mp49.8 MB
~Get Your Files Here !/01 - Introduction/01 - Full-stack deep learning, MLOps, and MLflow.srt12.5 KB
~Get Your Files Here !/01 - Introduction/02 - Prerequisites.mp4898.8 KB
~Get Your Files Here !/01 - Introduction/02 - Prerequisites.srt1.1 KB
~Get Your Files Here !/02 - 1. An Overview of Full-Stack Deep Learning/01 - Introducing full-stack deep learning.mp47.8 MB
~Get Your Files Here !/02 - 1. An Overview of Full-Stack Deep Learning/01 - Introducing full-stack deep learning.srt11.4 KB
~Get Your Files Here !/02 - 1. An Overview of Full-Stack Deep Learning/02 - Introducing MLOps.mp46.6 MB
~Get Your Files Here !/02 - 1. An Overview of Full-Stack Deep Learning/02 - Introducing MLOps.srt7.6 KB
~Get Your Files Here !/02 - 1. An Overview of Full-Stack Deep Learning/03 - Introducing MLflow.mp46.3 MB
~Get Your Files Here !/02 - 1. An Overview of Full-Stack Deep Learning/03 - Introducing MLflow.srt7.9 KB
~Get Your Files Here !/02 - 1. An Overview of Full-Stack Deep Learning/04 - Setting up the environment on Google Colab.mp413 MB
~Get Your Files Here !/02 - 1. An Overview of Full-Stack Deep Learning/04 - Setting up the environment on Google Colab.srt9.2 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.mp410.3 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.srt9.7 KB
~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/01 - Loading and exploring the EMNIST dataset.mp49.9 MB
~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/01 - Loading and exploring the EMNIST dataset.srt8.8 KB
~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/02 - Logging metrics, parameters, and artifacts in MLflow.mp411 MB
~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/02 - Logging metrics, parameters, and artifacts in MLflow.srt11 KB
~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/03 - Set up the dataset and data loader.mp46.9 MB
~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/03 - Set up the dataset and data loader.srt6.4 KB
~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/04 - Configuring the image classification DNN model.mp410.5 MB
~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/04 - Configuring the image classification DNN model.srt8.7 KB
~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/05 - Training a model within an MLflow run.mp411.1 MB
~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/05 - Training a model within an MLflow run.srt7 KB
~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/06 - Exploring parameters and metrics in MLflow.mp49 MB
~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/06 - Exploring parameters and metrics in MLflow.srt7.9 KB
~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/07 - Making predictions using MLflow artifacts.mp411.4 MB
~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/07 - Making predictions using MLflow artifacts.srt8.8 KB
~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/01 - Preparing data for image classification using CNN.mp49.7 MB
~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/01 - Preparing data for image classification using CNN.srt6.9 KB
~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/02 - Configuring and training the model using MLflow runs.mp415.5 MB
~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/02 - Configuring and training the model using MLflow runs.srt10.9 KB
~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/03 - Visualizing charts, metrics, and parameters on MLflow.mp415.2 MB
~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/03 - Visualizing charts, metrics, and parameters on MLflow.srt12 KB
~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/04 - Setting up the objective function for hyperparameter tuning.mp412.4 MB
~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/04 - Setting up the objective function for hyperparameter tuning.srt9.8 KB
~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/05 - Hyperparameter optimization with Hyperopt and MLflow.mp413.9 MB
~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/05 - Hyperparameter optimization with Hyperopt and MLflow.srt11.7 KB
~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/06 - Identifying the best model.mp47.8 MB
~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/06 - Identifying the best model.srt6 KB
~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/07 - Registering a model with the MLflow registry.mp45.7 MB
~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/07 - Registering a model with the MLflow registry.srt6 KB
~Get Your Files Here !/05 - 4. Model Deployment and Predictions/01 - Setting up MLflow on the local machine.mp48.2 MB
~Get Your Files Here !/05 - 4. Model Deployment and Predictions/01 - Setting up MLflow on the local machine.srt8.4 KB
~Get Your Files Here !/05 - 4. Model Deployment and Predictions/02 - Workaround to get model artifacts on the local machine.mp44.3 MB
~Get Your Files Here !/05 - 4. Model Deployment and Predictions/02 - Workaround to get model artifacts on the local machine.srt3.9 KB
~Get Your Files Here !/05 - 4. Model Deployment and Predictions/03 - Deploying and serving the model locally.mp413.8 MB
~Get Your Files Here !/05 - 4. Model Deployment and Predictions/03 - Deploying and serving the model locally.srt10.6 KB
~Get Your Files Here !/06 - Conclusion/01 - Summary and next steps.mp42.5 MB
~Get Your Files Here !/06 - Conclusion/01 - Summary and next steps.srt3.2 KB
~Get Your Files Here !/Bonus Resources.txt386 B
~Get Your Files Here !/Ex_Files_Full_Stack_Deep_Learning_Python/Exercise Files/final_code/datasets/emnist-letters-test.csv27.3 MB
~Get Your Files Here !/Ex_Files_Full_Stack_Deep_Learning_Python/Exercise Files/final_code/datasets/emnist-letters-train.csv163.7 MB
~Get Your Files Here !/Ex_Files_Full_Stack_Deep_Learning_Python/Exercise Files/final_code/demo_01_EMNISTClassificationUsingDNN.ipynb1.7 MB
~Get Your Files Here !/Ex_Files_Full_Stack_Deep_Learning_Python/Exercise Files/final_code/demo_02_EMNISTClassificationUsingCNN.ipynb3.1 MB
~Get Your Files Here !/Ex_Files_Full_Stack_Deep_Learning_Python/Exercise Files/final_code/demo_03_ModelDeployment.ipynb37.7 KB
~Get Your Files Here !/Ex_Files_Full_Stack_Deep_Learning_Python/Exercise Files/final_code/ipynb_checkpoints/demo_01_EMNISTClassificationUsingDNN-checkpoint.ipynb1.7 MB
~Get Your Files Here !/Ex_Files_Full_Stack_Deep_Learning_Python/Exercise Files/final_code/ipynb_checkpoints/demo_03_ModelDeployment-checkpoint.ipynb46.3 KB

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