ZerotoMastery - AI Engineering Bootcamp - Build, Train and Deploy Models with AWS ...
1.9 GB | 00:18:34 | mp4 | 1920X1080 | 16:9
Genre:eLearning |Language:English
Files Included :
01 AI Engineering Bootcamp Learn AWS SageMaker with Patrik Szepesi - Zer - 1920x1080 2055K (17.13 MB)
02 Course Introduction - Zer - 1920x1080 278K (17.41 MB)
03 Setting Up Our AWS Account - Zer - 1920x1080 441K (13.03 MB)
04 Set Up IAM Roles + Best Practices - Zer - 1920x1080 484K (23.32 MB)
05 AWS Security Best Practices - Zer - 1920x1080 468K (21.99 MB)
06 Set Up AWS SageMaker Domain - Zer - 1920x1080 453K (6.52 MB)
07 UI Domain Change - Zer - 1920x1080 606K (2.46 MB)
08 Setting Up SageMaker Environment - Zer - 1920x1080 416K (13.22 MB)
09 SageMaker Studio and Pricing - Zer - 1920x1080 429K (28.39 MB)
10 Setup SageMaker Server + PyTorch - Zer - 1920x1080 342K (15.82 MB)
11 HuggingFace Models, Sentiment Analysis, and AutoScaling - Zer - 1920x1080 703K (91.79 MB)
12 Get Dataset for Multiclass Text Classification - Zer - 1920x1080 337K (14.89 MB)
13 Creating Our AWS S3 Bucket - Zer - 1920x1080 445K (12.07 MB)
14 Uploading Our Training Data to S3 - Zer - 1920x1080 497K (4.61 MB)
15 Exploratory Data Analysis - Part 1 - Zer - 1920x1080 422K (40.04 MB)
16 Exploratory Data Analysis - Part 2 - Zer - 1920x1080 323K (13.77 MB)
17 Data Visualization and Best Practices - Zer - 1920x1080 296K (25.99 MB)
18 Setting Up Our Training Job Notebook + Reasons to Use SageMaker - Zer - 1920x1080 457K (55.7 MB)
19 Python Script for HuggingFace Estimator - Zer - 1920x1080 254K (28.22 MB)
20 Creating Our Optional Experiment Notebook - Part 1 - Zer - 1920x1080 441K (9.67 MB)
21 Creating Our Optional Experiment Notebook - Part 2 - Zer - 1920x1080 747K (18.57 MB)
22 Encoding Categorical Labels to Numeric Values - Zer - 1920x1080 453K (39.89 MB)
23 Understanding the Tokenization Vocabulary - Zer - 1920x1080 286K (30.06 MB)
24 Encoding Tokens - Zer - 1920x1080 318K (25.2 MB)
25 Practical Example of Tokenization and Encoding - Zer - 1920x1080 395K (32.68 MB)
26 Creating Our Dataset Loader Class - Zer - 1920x1080 390K (44.58 MB)
27 Setting Pytorch DataLoader - Zer - 1920x1080 337K (36.75 MB)
28 Which Path Will You Take - Zer - 1920x1080 227K (2.42 MB)
29 DistilBert vs Bert Differences - Zer - 1920x1080 234K (7.69 MB)
30 Embeddings In A Continuous Vector Space - Zer - 1920x1080 240K (12.86 MB)
31 Introduction To Positional Encodings - Zer - 1920x1080 229K (8.34 MB)
32 Positional Encodings - Part 1 - Zer - 1920x1080 384K (10.12 MB)
33 Positional Encodings - Part 2 (Even and Odd Indices) - Zer - 1920x1080 297K (20.91 MB)
34 Why Use Sine and Cosine Functions - Zer - 1920x1080 337K (12.22 MB)
35 Understanding the Nature of Sine and Cosine Functions - Zer - 1920x1080 419K (26.88 MB)
36 Visualizing Positional Encodings in Sine and Cosine Graphs - Zer - 1920x1080 404K (25.24 MB)
37 Solving the Equations to Get the Values for Positional Encodings - Zer - 1920x1080 324K (39.19 MB)
38 Introduction to Attention Mechanism - Zer - 1920x1080 245K (5.15 MB)
39 Query, Key and Value Matrix - Zer - 1920x1080 236K (29.56 MB)
40 Getting Started with Our Step by Step Attention Calculation - Zer - 1920x1080 249K (13.03 MB)
41 Calculating Key Vectors - Zer - 1920x1080 349K (52.35 MB)
42 Query Matrix Introduction - Zer - 1920x1080 293K (23.68 MB)
43 Calculating Raw Attention Scores - Zer - 1920x1080 295K (48.01 MB)
44 Understanding the Mathematics Behind Dot Products and Vector Alignment - Zer - 1920x1080 328K (31.54 MB)
45 Visualizing Raw Attention Scores in 2D - Zer - 1920x1080 310K (12.97 MB)
46 Converting Raw Attention Scores to Probability Distributions with Softmax - Zer - 1920x1080 379K (23.98 MB)
47 Normalization - Zer - 1920x1080 304K (7.58 MB)
48 Understanding the Value Matrix and Value Vector - Zer - 1920x1080 296K (21.25 MB)
49 Calculating the Final Context Aware Rich Representation for the Word River - Zer - 1920x1080 430K (33.73 MB)
50 Understanding the Output - Zer - 1920x1080 497K (5.35 MB)
51 Understanding Multi Head Attention - Zer - 1920x1080 345K (30.02 MB)
52 Multi Head Attention Example and Subsequent Layers - Zer - 1920x1080 446K (33.06 MB)
53 Masked Language Learning - Zer - 1920x1080 164K (3.22 MB)
54 Exercise Imposter Syndrome - Zer - 1920x1080 894K (10.49 MB)
55 Creating Our Custom Model Architecture with PyTorch - Zer - 1920x1080 293K (37.18 MB)
56 Adding the Dropout, Linear Layer, and ReLU to Our Model - Zer - 1920x1080 317K (33.41 MB)
57 Creating Our Accuracy Function - Zer - 1920x1080 296K (27.98 MB)
58 Creating Our Train Function - Zer - 1920x1080 355K (47.6 MB)
59 Finishing Our Train Function - Zer - 1920x1080 367K (20.46 MB)
60 Setting Up the Validation Function - Zer - 1920x1080 354K (34.91 MB)
61 Passing Parameters In SageMaker - Zer - 1920x1080 416K (11.38 MB)
62 Setting Up Model Parameters For Training - Zer - 1920x1080 296K (9.94 MB)
63 Understanding The Mathematics Behind Cross Entropy Loss - Zer - 1920x1080 359K (13.68 MB)
64 Finishing Our Script py File - Zer - 1920x1080 412K (20.76 MB)
65 Quota Increase - Zer - 1920x1080 549K (24.8 MB)
66 Starting Our Training Job - Zer - 1920x1080 863K (44.47 MB)
67 Debugging Our Training Job With AWS CloudWatch - Zer - 1920x1080 606K (58.12 MB)
68 Analyzing Our Training Job Results - Zer - 1920x1080 707K (29.74 MB)
69 Creating Our Inference Script For Our PyTorch Model - Zer - 1920x1080 324K (19.53 MB)
70 Finishing Our PyTorch Inference Script - Zer - 1920x1080 365K (23.4 MB)
71 Setting Up Our Deployment - Zer - 1920x1080 476K (26 MB)
72 Deploying Our Model To A SageMaker Endpoint - Zer - 1920x1080 631K (36.25 MB)
73 Introduction to Endpoint Load Testing - Zero To Mastery Academy - 1920x1080 213K (7.86 MB)
74 Creating Our Test Data for Load Testing - Zero To Mastery Academy - 1920x1080 230K (18.54 MB)
75 Upload Testing Data to S3 - Zero To Mastery Academy - 1920x1080 715K (4.5 MB)
76 Creating Our Model for Load Testing - Zero To Mastery Academy - 1920x1080 782K (18.79 MB)
77 Starting Our Load Test Job - Zero To Mastery Academy - 1920x1080 621K (27.52 MB)
78 Analyze Load Test Results - Zero To Mastery Academy - 1920x1080 425K (28.17 MB)
79 Deploying Our Endpoint - Zero To Mastery Academy - 1920x1080 538K (14.36 MB)
80 Creating Lambda Function to Call Our Endpoint - Zero To Mastery Academy - 1920x1080 412K (28.19 MB)
81 Setting Up Our AWS API Gateway - Zero To Mastery Academy - 1920x1080 449K (15.86 MB)
82 Testing Our Model with Postman, API Gateway and Lambda - Zero To Mastery Academy - 1920x1080 518K (19.98 MB)
83 Cleaning Up Resources - Zero To Mastery Academy - 1920x1080 421K (8.29 MB)
84 Thank You! - Zero To Mastery Academy - 1920x1080 1046K (4.25 MB)
02 Course Introduction - Zer - 1920x1080 278K (17.41 MB)
03 Setting Up Our AWS Account - Zer - 1920x1080 441K (13.03 MB)
04 Set Up IAM Roles + Best Practices - Zer - 1920x1080 484K (23.32 MB)
05 AWS Security Best Practices - Zer - 1920x1080 468K (21.99 MB)
06 Set Up AWS SageMaker Domain - Zer - 1920x1080 453K (6.52 MB)
07 UI Domain Change - Zer - 1920x1080 606K (2.46 MB)
08 Setting Up SageMaker Environment - Zer - 1920x1080 416K (13.22 MB)
09 SageMaker Studio and Pricing - Zer - 1920x1080 429K (28.39 MB)
10 Setup SageMaker Server + PyTorch - Zer - 1920x1080 342K (15.82 MB)
11 HuggingFace Models, Sentiment Analysis, and AutoScaling - Zer - 1920x1080 703K (91.79 MB)
12 Get Dataset for Multiclass Text Classification - Zer - 1920x1080 337K (14.89 MB)
13 Creating Our AWS S3 Bucket - Zer - 1920x1080 445K (12.07 MB)
14 Uploading Our Training Data to S3 - Zer - 1920x1080 497K (4.61 MB)
15 Exploratory Data Analysis - Part 1 - Zer - 1920x1080 422K (40.04 MB)
16 Exploratory Data Analysis - Part 2 - Zer - 1920x1080 323K (13.77 MB)
17 Data Visualization and Best Practices - Zer - 1920x1080 296K (25.99 MB)
18 Setting Up Our Training Job Notebook + Reasons to Use SageMaker - Zer - 1920x1080 457K (55.7 MB)
19 Python Script for HuggingFace Estimator - Zer - 1920x1080 254K (28.22 MB)
20 Creating Our Optional Experiment Notebook - Part 1 - Zer - 1920x1080 441K (9.67 MB)
21 Creating Our Optional Experiment Notebook - Part 2 - Zer - 1920x1080 747K (18.57 MB)
22 Encoding Categorical Labels to Numeric Values - Zer - 1920x1080 453K (39.89 MB)
23 Understanding the Tokenization Vocabulary - Zer - 1920x1080 286K (30.06 MB)
24 Encoding Tokens - Zer - 1920x1080 318K (25.2 MB)
25 Practical Example of Tokenization and Encoding - Zer - 1920x1080 395K (32.68 MB)
26 Creating Our Dataset Loader Class - Zer - 1920x1080 390K (44.58 MB)
27 Setting Pytorch DataLoader - Zer - 1920x1080 337K (36.75 MB)
28 Which Path Will You Take - Zer - 1920x1080 227K (2.42 MB)
29 DistilBert vs Bert Differences - Zer - 1920x1080 234K (7.69 MB)
30 Embeddings In A Continuous Vector Space - Zer - 1920x1080 240K (12.86 MB)
31 Introduction To Positional Encodings - Zer - 1920x1080 229K (8.34 MB)
32 Positional Encodings - Part 1 - Zer - 1920x1080 384K (10.12 MB)
33 Positional Encodings - Part 2 (Even and Odd Indices) - Zer - 1920x1080 297K (20.91 MB)
34 Why Use Sine and Cosine Functions - Zer - 1920x1080 337K (12.22 MB)
35 Understanding the Nature of Sine and Cosine Functions - Zer - 1920x1080 419K (26.88 MB)
36 Visualizing Positional Encodings in Sine and Cosine Graphs - Zer - 1920x1080 404K (25.24 MB)
37 Solving the Equations to Get the Values for Positional Encodings - Zer - 1920x1080 324K (39.19 MB)
38 Introduction to Attention Mechanism - Zer - 1920x1080 245K (5.15 MB)
39 Query, Key and Value Matrix - Zer - 1920x1080 236K (29.56 MB)
40 Getting Started with Our Step by Step Attention Calculation - Zer - 1920x1080 249K (13.03 MB)
41 Calculating Key Vectors - Zer - 1920x1080 349K (52.35 MB)
42 Query Matrix Introduction - Zer - 1920x1080 293K (23.68 MB)
43 Calculating Raw Attention Scores - Zer - 1920x1080 295K (48.01 MB)
44 Understanding the Mathematics Behind Dot Products and Vector Alignment - Zer - 1920x1080 328K (31.54 MB)
45 Visualizing Raw Attention Scores in 2D - Zer - 1920x1080 310K (12.97 MB)
46 Converting Raw Attention Scores to Probability Distributions with Softmax - Zer - 1920x1080 379K (23.98 MB)
47 Normalization - Zer - 1920x1080 304K (7.58 MB)
48 Understanding the Value Matrix and Value Vector - Zer - 1920x1080 296K (21.25 MB)
49 Calculating the Final Context Aware Rich Representation for the Word River - Zer - 1920x1080 430K (33.73 MB)
50 Understanding the Output - Zer - 1920x1080 497K (5.35 MB)
51 Understanding Multi Head Attention - Zer - 1920x1080 345K (30.02 MB)
52 Multi Head Attention Example and Subsequent Layers - Zer - 1920x1080 446K (33.06 MB)
53 Masked Language Learning - Zer - 1920x1080 164K (3.22 MB)
54 Exercise Imposter Syndrome - Zer - 1920x1080 894K (10.49 MB)
55 Creating Our Custom Model Architecture with PyTorch - Zer - 1920x1080 293K (37.18 MB)
56 Adding the Dropout, Linear Layer, and ReLU to Our Model - Zer - 1920x1080 317K (33.41 MB)
57 Creating Our Accuracy Function - Zer - 1920x1080 296K (27.98 MB)
58 Creating Our Train Function - Zer - 1920x1080 355K (47.6 MB)
59 Finishing Our Train Function - Zer - 1920x1080 367K (20.46 MB)
60 Setting Up the Validation Function - Zer - 1920x1080 354K (34.91 MB)
61 Passing Parameters In SageMaker - Zer - 1920x1080 416K (11.38 MB)
62 Setting Up Model Parameters For Training - Zer - 1920x1080 296K (9.94 MB)
63 Understanding The Mathematics Behind Cross Entropy Loss - Zer - 1920x1080 359K (13.68 MB)
64 Finishing Our Script py File - Zer - 1920x1080 412K (20.76 MB)
65 Quota Increase - Zer - 1920x1080 549K (24.8 MB)
66 Starting Our Training Job - Zer - 1920x1080 863K (44.47 MB)
67 Debugging Our Training Job With AWS CloudWatch - Zer - 1920x1080 606K (58.12 MB)
68 Analyzing Our Training Job Results - Zer - 1920x1080 707K (29.74 MB)
69 Creating Our Inference Script For Our PyTorch Model - Zer - 1920x1080 324K (19.53 MB)
70 Finishing Our PyTorch Inference Script - Zer - 1920x1080 365K (23.4 MB)
71 Setting Up Our Deployment - Zer - 1920x1080 476K (26 MB)
72 Deploying Our Model To A SageMaker Endpoint - Zer - 1920x1080 631K (36.25 MB)
73 Introduction to Endpoint Load Testing - Zero To Mastery Academy - 1920x1080 213K (7.86 MB)
74 Creating Our Test Data for Load Testing - Zero To Mastery Academy - 1920x1080 230K (18.54 MB)
75 Upload Testing Data to S3 - Zero To Mastery Academy - 1920x1080 715K (4.5 MB)
76 Creating Our Model for Load Testing - Zero To Mastery Academy - 1920x1080 782K (18.79 MB)
77 Starting Our Load Test Job - Zero To Mastery Academy - 1920x1080 621K (27.52 MB)
78 Analyze Load Test Results - Zero To Mastery Academy - 1920x1080 425K (28.17 MB)
79 Deploying Our Endpoint - Zero To Mastery Academy - 1920x1080 538K (14.36 MB)
80 Creating Lambda Function to Call Our Endpoint - Zero To Mastery Academy - 1920x1080 412K (28.19 MB)
81 Setting Up Our AWS API Gateway - Zero To Mastery Academy - 1920x1080 449K (15.86 MB)
82 Testing Our Model with Postman, API Gateway and Lambda - Zero To Mastery Academy - 1920x1080 518K (19.98 MB)
83 Cleaning Up Resources - Zero To Mastery Academy - 1920x1080 421K (8.29 MB)
84 Thank You! - Zero To Mastery Academy - 1920x1080 1046K (4.25 MB)
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