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AWS SageMaker Practical for Beginners. Build 6 Projects
大小 8.98 GB
文件数 97
Info Hash: 1F373A4D53F676FC15686F8F75A02E9CD66D165A
收录时间 2026-01-14 15:43:05
更新时间 2026-01-14 15:43:05
文件列表 (97)
1 - Introduction, Success Tips & Best Practices and Key Learning Outcomes/01 - Course Introduction and Welcome Message.mp4
24.54 MB
1 - Introduction, Success Tips & Best Practices and Key Learning Outcomes/02 - Updates on Udemy Reviews.mp4
5.93 MB
1 - Introduction, Success Tips & Best Practices and Key Learning Outcomes/03 - Course Key Tips and Best Practices.mp4
51.13 MB
1 - Introduction, Success Tips & Best Practices and Key Learning Outcomes/04 - Course Outline and Key Learning Outcomes.mp4
156.07 MB
2 - Introduction to AI_ML, AWS and Cloud Computing/05 - AWS Free Tier Account Setup and Overview.mp4
33.02 MB
2 - Introduction to AI_ML, AWS and Cloud Computing/06 - Introduction to AI, Machine Learning and Deep Learning.mp4
106.47 MB
2 - Introduction to AI_ML, AWS and Cloud Computing/07 - Introduction to AI, Machine Learning and Deep Learning - Part #2.mp4
111.11 MB
2 - Introduction to AI_ML, AWS and Cloud Computing/08 - Good Data Vs. Bad Data.mp4
46.46 MB
2 - Introduction to AI_ML, AWS and Cloud Computing/09 - Introduction to AWS and Cloud Computing.mp4
71.38 MB
2 - Introduction to AI_ML, AWS and Cloud Computing/10 - Key Machine Learning Components and AWS Management Console Tour.mp4
42.05 MB
2 - Introduction to AI_ML, AWS and Cloud Computing/11 - AWS Regions and Availability Zones.mp4
57.71 MB
2 - Introduction to AI_ML, AWS and Cloud Computing/12 - Amazon S3.mp4
88.88 MB
2 - Introduction to AI_ML, AWS and Cloud Computing/13 - Amazon EC2 and IAM.mp4
82.78 MB
2 - Introduction to AI_ML, AWS and Cloud Computing/14 - AWS SageMaker Overview.mp4
38.44 MB
2 - Introduction to AI_ML, AWS and Cloud Computing/15 - AWS SageMaker Walk-through.mp4
118.16 MB
2 - Introduction to AI_ML, AWS and Cloud Computing/16 - AWS SageMaker Studio Overview.mp4
47.64 MB
2 - Introduction to AI_ML, AWS and Cloud Computing/17 - AWS SageMaker Studio Walk-through.mp4
77.75 MB
2 - Introduction to AI_ML, AWS and Cloud Computing/18 - SageMaker Models Deployment.mp4
133.81 MB
3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/19 - Project Overview.mp4
21.34 MB
3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/20 - Simple Linear Regression Intuition.mp4
60.3 MB
3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/21 - Least Sum of Squares.mp4
52.16 MB
3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/22 - AWS SageMaker Linear Learner Overview.mp4
168.2 MB
3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/23 - Coding Task #1A - Instantiate AWS SageMaker Notebook Instance (Method #1).mp4
195.42 MB
3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/24 - Coding Task #1B - Using AWS SageMaker Studio (Method #2).mp4
88.43 MB
3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/25 - Coding Task #2 - Import Key libraries and dataset.mp4
67.48 MB
3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/26 - Coding Task #3 - Perform Exploratory Data Analysis.mp4
144.04 MB
3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/27 - Coding Task #4 - Create Training and Testing Dataset.mp4
91.98 MB
3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/28 - Coding Task #5 - Train a Linear Regression Model in SkLearn.mp4
74.29 MB
3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/29 - Coding Task #6 - Evaluate Trained Model Performance.mp4
62.73 MB
3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/30 - Coding Task #7 - Train a Linear Learner Model in AWS SageMaker.mp4
483.72 MB
3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/31 - Coding Task #8 - Deploy Model & invoke endpoint in SageMaker.mp4
125.12 MB
4 - Project #2 - Medical Insurance Premium Prediction/32 - Project Overview and Introduction.mp4
11.44 MB
4 - Project #2 - Medical Insurance Premium Prediction/33 - Multiple Linear Regression Intuition.mp4
20.82 MB
4 - Project #2 - Medical Insurance Premium Prediction/34 - Regression Metrics and KPIs - RMSE, MSE, MAE, MAPE.mp4
83.4 MB
4 - Project #2 - Medical Insurance Premium Prediction/35 - Regression Metrics and KPIs - R2 and Adjusted R2.mp4
83.01 MB
4 - Project #2 - Medical Insurance Premium Prediction/36 - Coding Task #1 & #2 - Import Dataset and Key Libraries.mp4
136.07 MB
4 - Project #2 - Medical Insurance Premium Prediction/37 - Coding Task #3 - Perform Exploratory Data Analysis.mp4
158.23 MB
4 - Project #2 - Medical Insurance Premium Prediction/38 - Coding Task #4 - Perform Data Visualization.mp4
112.73 MB
4 - Project #2 - Medical Insurance Premium Prediction/39 - Coding Task #5 - Create Training and Testing Datasets.mp4
75.77 MB
4 - Project #2 - Medical Insurance Premium Prediction/40 - Coding Task #6 - Train a Machine Learning Model Locally.mp4
57.93 MB
4 - Project #2 - Medical Insurance Premium Prediction/41 - Coding Task #7 - Train a Linear Learner Model in AWS SageMaker.mp4
344.44 MB
4 - Project #2 - Medical Insurance Premium Prediction/42 - Coding Task #8 - Deploy Trained Model and Invoke Endpoint.mp4
111.42 MB
4 - Project #2 - Medical Insurance Premium Prediction/43 - Artificial Neural Networks for Regression Tasks.mp4
70.23 MB
4 - Project #2 - Medical Insurance Premium Prediction/44 - Activation Functions - Sigmoid, RELU and Tanh.mp4
20.03 MB
4 - Project #2 - Medical Insurance Premium Prediction/45 - Multilayer Perceptron Networks.mp4
19.64 MB
4 - Project #2 - Medical Insurance Premium Prediction/46 - How do Artificial Neural Networks Train.mp4
41.44 MB
4 - Project #2 - Medical Insurance Premium Prediction/47 - Gradient Descent Algorithm.mp4
105.63 MB
4 - Project #2 - Medical Insurance Premium Prediction/48 - Backpropagation Algorithm.mp4
22.82 MB
4 - Project #2 - Medical Insurance Premium Prediction/49 - Coding Task #9 - Train Artificial Neural Networks for Regression Tasks.mp4
250.2 MB
5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/50 - Introduction to Case Study.mp4
73.16 MB
5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/51 - Basics - What is the difference between Bias & Variance.mp4
66.42 MB
5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/52 - Basics - L1 & L2 Regularization - Part #1.mp4
32.15 MB
5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/53 - Basics - L1 & L2 Regularization - Part #2.mp4
16.24 MB
5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/54 - Introduction to XGBoost (Extreme Gradient Boosting) algorithm.mp4
34.99 MB
5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/55 - What is Boosting.mp4
46.54 MB
5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/56 - Decision Trees and Ensemble Learning.mp4
35.98 MB
5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/57 - Gradient Boosted Trees - Deep Dive - Part #1.mp4
179.8 MB
5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/58 - Gradient Boosted Trees - Deep Dive - Part #2.mp4
76.52 MB
5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/59 - AWS SageMaker XGBoost Algorithm.mp4
55.81 MB
5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/60 - Project Introduction and Notebook Instance Instantiation.mp4
105.05 MB
5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/61 - Coding Task #1 #2 #3 - Load Dataset_Libraries and Perform Data Exploration.mp4
225.33 MB
5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/62 - Coding Task #4 - Merge and Manipulate DataFrame Using Pandas.mp4
73.62 MB
5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/63 - Coding Task #5 - Explore Merged Datasets.mp4
63.18 MB
5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/64 - Coding Task #6 #7 - Visualize Dataset.mp4
205.17 MB
5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/65 - Coding Task #8 - Prepare the Data To Perform Training.mp4
33.6 MB
5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/66 - Coding Task #9 - Train XGBoost Locally.mp4
84.81 MB
5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/67 - Coding Task #10 - Train XGBoost Using SageMaker.mp4
175.95 MB
5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/68 - Coding Task #11 - Deploy XGBoost endpoint and Make Predictions.mp4
69.15 MB
5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/69 - Coding Task #12 - Perform Hyperparameters Tuning.mp4
166.42 MB
5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/70 - Coding Task #13 - Retrain the Model Using best (optimized) Hyperparameters.mp4
97.57 MB
6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/71 - Introduction and Project Overview.mp4
98.53 MB
6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/72 - Principal Component Analysis (PCA) Intuition.mp4
111.75 MB
6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/73 - XGBoost for Classification Tasks (Review Lecture).mp4
54.98 MB
6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/74 - Confusion Matrix.mp4
53.47 MB
6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/75 - Precision, Recall, and F1-Score.mp4
207.3 MB
6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/76 - Area Under Curve (AUC) and Receiver Operating Characteristics (ROC) Metrics.mp4
41.98 MB
6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/77 - Overfitting and Under fitting Models.mp4
20.23 MB
6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/78 - Coding Task #1 - SageMaker Studio Notebook Setup.mp4
57.87 MB
6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/79 - Coding Task #2 & #3 - Import Data_Libraries & Perform Exploratory data analysis.mp4
89.06 MB
6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/80 - Coding Task #4 & #5 - Visualize Datasets & Prepare Training_Testing Data.mp4
90.84 MB
6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/81 - Coding Task #6 - Train & Test XGboost and Perform Grid Search (Local Mode).mp4
229.01 MB
6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/82 - Coding Task #7 - Train a PCA Model in AWS SageMaker.mp4
155.61 MB
6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/83 - Coding Task #8 - Deploy Trained PCA Model Endpoint & Envoke endpoint.mp4
93.77 MB
6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/84 - Coding Task #9 - Train XGBoost (SageMaker Built-in) to do Classification Tasks.mp4
115.47 MB
6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/85 - Coding Task #10 - Deploy Endpoint, Make Inference @ Test Model.mp4
83.07 MB
7 - Project #5 - Deep Learning for Traffic Sign Classification Using AWS SageMaker/86 - Project Overview and Introduction.mp4
96.8 MB
7 - Project #5 - Deep Learning for Traffic Sign Classification Using AWS SageMaker/87 - What are Convolutional Neural Networks and How do they Learn - Part #1.mp4
118.08 MB
7 - Project #5 - Deep Learning for Traffic Sign Classification Using AWS SageMaker/88 - What are Convolutional Neural Networks and How do they Learn - Part #2.mp4
124.29 MB
7 - Project #5 - Deep Learning for Traffic Sign Classification Using AWS SageMaker/89 - How to Improve CNNs Performance.mp4
13.27 MB
7 - Project #5 - Deep Learning for Traffic Sign Classification Using AWS SageMaker/90 - Confusion Matrix.mp4
40.48 MB
7 - Project #5 - Deep Learning for Traffic Sign Classification Using AWS SageMaker/91 - LeNet Network Architecture.mp4
85.72 MB
7 - Project #5 - Deep Learning for Traffic Sign Classification Using AWS SageMaker/92 - Request AWS SageMaker Service Limit Increase.mp4
4.99 MB
7 - Project #5 - Deep Learning for Traffic Sign Classification Using AWS SageMaker/93 - Coding Part #1 #2 - Import Images and Visualize Them.mp4
157.85 MB
7 - Project #5 - Deep Learning for Traffic Sign Classification Using AWS SageMaker/94 - Coding #3 #4 - Upload Training_Testing Data to S3.mp4
56.04 MB
7 - Project #5 - Deep Learning for Traffic Sign Classification Using AWS SageMaker/95 - Coding Task #5 - Build and Train CNNs.mp4
206.11 MB
7 - Project #5 - Deep Learning for Traffic Sign Classification Using AWS SageMaker/96 - Coding Task #6 - Deploy Trained Model Using SageMaker.mp4
70.47 MB
SageMaker+Practical+Course+Package.zip
145.15 MB
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