AWS SageMaker Practical for Beginners Build Projects | 9CF42EC09D167BA3B6D7481C9917AECA1DBF3112

AWS SageMaker Practical for Beginners Build Projects

Name	AWS SageMaker Practical for Beginners. Build 6 Projects	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	9.6 GB
Total Files	99
Last Seen	2025-07-17 23:40
Hash	9CF42EC09D167BA3B6D7481C9917AECA1DBF3112

/.../3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/
30 - Coding Task #7 - Train a Linear Learner Model in AWS SageMaker.mp4	507.2 MB
19 - Project Overview.mp4	22.4 MB
20 - Simple Linear Regression Intuition.mp4	63.2 MB
21 - Least Sum of Squares.mp4	54.7 MB
22 - AWS SageMaker Linear Learner Overview.mp4	176.4 MB
23 - Coding Task #1A - Instantiate AWS SageMaker Notebook Instance (Method #1).mp4	204.9 MB
24 - Coding Task #1B - Using AWS SageMaker Studio (Method #2).mp4	92.7 MB
25 - Coding Task #2 - Import Key libraries and dataset.mp4	70.8 MB
26 - Coding Task #3 - Perform Exploratory Data Analysis.mp4	151.0 MB
27 - Coding Task #4 - Create Training and Testing Dataset.mp4	96.4 MB
28 - Coding Task #5 - Train a Linear Regression Model in SkLearn.mp4	77.9 MB
29 - Coding Task #6 - Evaluate Trained Model Performance.mp4	65.8 MB
31 - Coding Task #8 - Deploy Model & invoke endpoint in SageMaker.mp4	131.2 MB
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TutsNode.com.txt	0.1 KB
[TGx]Downloaded from torrentgalaxy.to .txt	0.6 KB
/[TutsNode.com] - AWS SageMaker Practical for Beginners/
SageMaker+Practical+Course+Package.zip	152.2 MB
/.../1 - Introduction, Success Tips & Best Practices and Key Learning Outcomes/
01 - Course Introduction and Welcome Message.mp4	25.7 MB
02 - Updates on Udemy Reviews.mp4	6.2 MB
03 - Course Key Tips and Best Practices.mp4	53.6 MB
04 - Course Outline and Key Learning Outcomes.mp4	163.7 MB
/.../2 - Introduction to AI_ML, AWS and Cloud Computing/
05 - AWS Free Tier Account Setup and Overview.mp4	34.6 MB
06 - Introduction to AI, Machine Learning and Deep Learning.mp4	111.6 MB
07 - Introduction to AI, Machine Learning and Deep Learning - Part #2.mp4	116.5 MB
08 - Good Data Vs. Bad Data.mp4	48.7 MB
09 - Introduction to AWS and Cloud Computing.mp4	74.8 MB
10 - Key Machine Learning Components and AWS Management Console Tour.mp4	44.1 MB
11 - AWS Regions and Availability Zones.mp4	60.5 MB
12 - Amazon S3.mp4	93.2 MB
13 - Amazon EC2 and IAM.mp4	86.8 MB
14 - AWS SageMaker Overview.mp4	40.3 MB
15 - AWS SageMaker Walk-through.mp4	123.9 MB
16 - AWS SageMaker Studio Overview.mp4	50.0 MB
17 - AWS SageMaker Studio Walk-through.mp4	81.5 MB
18 - SageMaker Models Deployment.mp4	140.3 MB
/.../4 - Project #2 - Medical Insurance Premium Prediction/
32 - Project Overview and Introduction.mp4	12.0 MB
33 - Multiple Linear Regression Intuition.mp4	21.8 MB
34 - Regression Metrics and KPIs - RMSE, MSE, MAE, MAPE.mp4	87.5 MB
35 - Regression Metrics and KPIs - R2 and Adjusted R2.mp4	87.0 MB
36 - Coding Task #1 & #2 - Import Dataset and Key Libraries.mp4	142.7 MB
37 - Coding Task #3 - Perform Exploratory Data Analysis.mp4	165.9 MB
38 - Coding Task #4 - Perform Data Visualization.mp4	118.2 MB
39 - Coding Task #5 - Create Training and Testing Datasets.mp4	79.4 MB
40 - Coding Task #6 - Train a Machine Learning Model Locally.mp4	60.7 MB
41 - Coding Task #7 - Train a Linear Learner Model in AWS SageMaker.mp4	361.2 MB
42 - Coding Task #8 - Deploy Trained Model and Invoke Endpoint.mp4	116.8 MB
43 - Artificial Neural Networks for Regression Tasks.mp4	73.6 MB
44 - Activation Functions - Sigmoid, RELU and Tanh.mp4	21.0 MB
45 - Multilayer Perceptron Networks.mp4	20.6 MB
46 - How do Artificial Neural Networks Train.mp4	43.5 MB
47 - Gradient Descent Algorithm.mp4	110.8 MB
48 - Backpropagation Algorithm.mp4	23.9 MB
49 - Coding Task #9 - Train Artificial Neural Networks for Regression Tasks.mp4	262.4 MB
/.../5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/
50 - Introduction to Case Study.mp4	76.7 MB
51 - Basics - What is the difference between Bias & Variance.mp4	69.6 MB
52 - Basics - L1 & L2 Regularization - Part #1.mp4	33.7 MB
53 - Basics - L1 & L2 Regularization - Part #2.mp4	17.0 MB
54 - Introduction to XGBoost (Extreme Gradient Boosting) algorithm.mp4	36.7 MB
55 - What is Boosting.mp4	48.8 MB
56 - Decision Trees and Ensemble Learning.mp4	37.7 MB
57 - Gradient Boosted Trees - Deep Dive - Part #1.mp4	188.5 MB
58 - Gradient Boosted Trees - Deep Dive - Part #2.mp4	80.2 MB
59 - AWS SageMaker XGBoost Algorithm.mp4	58.5 MB
60 - Project Introduction and Notebook Instance Instantiation.mp4	110.2 MB
61 - Coding Task #1 #2 #3 - Load Dataset_Libraries and Perform Data Exploration.mp4	236.3 MB
62 - Coding Task #4 - Merge and Manipulate DataFrame Using Pandas.mp4	77.2 MB
63 - Coding Task #5 - Explore Merged Datasets.mp4	66.2 MB
64 - Coding Task #6 #7 - Visualize Dataset.mp4	215.1 MB
65 - Coding Task #8 - Prepare the Data To Perform Training.mp4	35.2 MB
66 - Coding Task #9 - Train XGBoost Locally.mp4	88.9 MB
67 - Coding Task #10 - Train XGBoost Using SageMaker.mp4	184.5 MB
68 - Coding Task #11 - Deploy XGBoost endpoint and Make Predictions.mp4	72.5 MB
69 - Coding Task #12 - Perform Hyperparameters Tuning.mp4	174.5 MB
70 - Coding Task #13 - Retrain the Model Using best (optimized) Hyperparameters.mp4	102.3 MB
/.../6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/
71 - Introduction and Project Overview.mp4	103.3 MB
72 - Principal Component Analysis (PCA) Intuition.mp4	117.2 MB
73 - XGBoost for Classification Tasks (Review Lecture).mp4	57.7 MB
74 - Confusion Matrix.mp4	56.1 MB
75 - Precision, Recall, and F1-Score.mp4	217.4 MB
76 - Area Under Curve (AUC) and Receiver Operating Characteristics (ROC) Metrics.mp4	44.0 MB
77 - Overfitting and Under fitting Models.mp4	21.2 MB
78 - Coding Task #1 - SageMaker Studio Notebook Setup.mp4	60.7 MB
79 - Coding Task #2 & #3 - Import Data_Libraries & Perform Exploratory data analysis.mp4	93.4 MB
80 - Coding Task #4 & #5 - Visualize Datasets & Prepare Training_Testing Data.mp4	95.2 MB
81 - Coding Task #6 - Train & Test XGboost and Perform Grid Search (Local Mode).mp4	240.1 MB
82 - Coding Task #7 - Train a PCA Model in AWS SageMaker.mp4	163.2 MB
83 - Coding Task #8 - Deploy Trained PCA Model Endpoint & Envoke endpoint.mp4	98.3 MB
84 - Coding Task #9 - Train XGBoost (SageMaker Built-in) to do Classification Tasks.mp4	121.1 MB
85 - Coding Task #10 - Deploy Endpoint, Make Inference @ Test Model.mp4	87.1 MB
/.../7 - Project #5 - Deep Learning for Traffic Sign Classification Using AWS SageMaker/
86 - Project Overview and Introduction.mp4	101.5 MB
87 - What are Convolutional Neural Networks and How do they Learn - Part #1.mp4	123.8 MB
88 - What are Convolutional Neural Networks and How do they Learn - Part #2.mp4	130.3 MB
89 - How to Improve CNNs Performance.mp4	13.9 MB
90 - Confusion Matrix.mp4	42.4 MB
91 - LeNet Network Architecture.mp4	89.9 MB
92 - Request AWS SageMaker Service Limit Increase.mp4	5.2 MB
93 - Coding Part #1 #2 - Import Images and Visualize Them.mp4	165.5 MB
94 - Coding #3 #4 - Upload Training_Testing Data to S3.mp4	58.8 MB
95 - Coding Task #5 - Build and Train CNNs.mp4	216.1 MB
96 - Coding Task #6 - Deploy Trained Model Using SageMaker.mp4	73.9 MB
Total files 99