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340 - AWS Certified Machine Learning - Specialty

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File Name
Size
001 - Course Introduction.mp4
41 MB
002 - About the Training Architect.mp4
22 MB
003 - About the Exam.mp4
152 MB
004 - Artificial Intelligence.mp4
21 MB
005 - What Is Machine Learning?.mp4
41 MB
006 - What Is Deep Learning?.mp4
39 MB
007 - Section Introduction.mp4
11 MB
008 - Machine Learning Lifecycle.mp4
60 MB
009 - Supervised, Unsupervised, and Reinforcement.mp4
41 MB
010 - Optimization.mp4
32 MB
011 - Regularization.mp4
16 MB
012 - Hyperparameters.mp4
24 MB
013 - Validation.mp4
15 MB
014 - Section Introduction.mp4
9.8 MB
015 - Feature Selection and Engineering.mp4
36 MB
016 - Principal Component Analysis (PCA).mp4
40 MB
017 - Missing and Unbalanced Data.mp4
43 MB
018 - Label and One Hot Encoding.mp4
15 MB
019 - Splitting and Randomization.mp4
17 MB
020 - RecordIO Format.mp4
21 MB
021 - Section Introduction.mp4
8.1 MB
022 - Logistical Regression.mp4
32 MB
023 - Linear Regression.mp4
24 MB
024 - Support Vector Machines.mp4
22 MB
025 - Decision Trees.mp4
39 MB
026 - Random Forests.mp4
26 MB
027 - K-Means.mp4
34 MB
028 - K-Nearest Neighbour.mp4
14 MB
029 - Latent Dirichlet Allocation (LDA) Algorithm.mp4
39 MB
030 - Section Introduction.mp4
8.0 MB
031 - Neural Networks.mp4
72 MB
032 - Convolutional Neural Networks (CNN).mp4
45 MB
033 - Recurrent Neural Networks (RNN).mp4
42 MB
034 - Section Introduction.mp4
17 MB
035 - Confusion Matrix.mp4
49 MB
036 - Sensitivity and Specificity.mp4
84 MB
037 - Accuracy and Precision.mp4
32 MB
038 - ROC_AUC.mp4
69 MB
039 - Gini Impurity.mp4
35 MB
040 - F1 Score.mp4
25 MB
041 - Introduction to Jupyter Notebooks.mp4
67 MB
042 - ML and DL Frameworks.mp4
40 MB
043 - TensorFlow.mp4
83 MB
044 - PyTorch.mp4
40 MB
045 - MXNet.mp4
32 MB
046 - Scikit-learn.mp4
94 MB
047 - S3.mp4
91 MB
048 - Glue.mp4
84 MB
049 - Athena.mp4
87 MB
050 - QuickSight.mp4
47 MB
051 - Kinesis, Streams, Firehose, Video, and Analytics.mp4
82 MB
052 - EMR with Spark.mp4
33 MB
053 - EC2 for ML.mp4
61 MB
054 - Amazon ML.mp4
13 MB
055 - Section Introduction.mp4
38 MB
056 - Amazon Rekognition (Images) Part 1.mp4
91 MB
057 - Amazon Rekognition (Images) Part 2 - the API.mp4
161 MB
058 - Amazon Rekognition (Video).mp4
48 MB
059 - Amazon Polly.mp4
52 MB
060 - Amazon Transcribe.mp4
53 MB
061 - Amazon Translate.mp4
89 MB
062 - Amazon Comprehend.mp4
72 MB
063 - Amazon Lex.mp4
78 MB
064 - Amazon Service Chaining with AWS Step Functions.mp4
66 MB
065 - Section Introduction.mp4
19 MB
066 - What is Amazon SageMaker?.mp4
40 MB
067 - The Three Stages.mp4
13 MB
068 - Control (Console_SDK_Notebooks).mp4
84 MB
069 - SageMaker Notebooks.mp4
96 MB
070 - Data Preprocessing.mp4
60 MB
071 - Ground Truth.mp4
40 MB
072 - Preprocessing Image Data (Pinehead NotPinehead).mp4
192 MB
073 - Algorithms.mp4
70 MB
074 - SageMaker Algorithms - Architecture 1.mp4
53 MB
075 - SageMaker Algorithms - Architecture 2.mp4
49 MB
076 - SageMaker Algorithms - Architecture 3.mp4
24 MB
077 - Training an Image Classifier - Part 1 (Pinehead NotPinehead).mp4
127 MB
078 - Training an Image Classifier - Part 2 (Pinehead NotPinehead).mp4
32 MB
079 - Hyperparameter Tuning.mp4
58 MB
080 - Inference Pipelines.mp4
18 MB
081 - Real-Time and Batch Inference.mp4
24 MB
082 - Deploy an Image Classifier (Pinehead, NotPinehead).mp4
110 MB
083 - Accessing Inference from Apps.mp4
17 MB
084 - Create a custom API for inference - Part 1 (Pinehead NotPinehead).mp4
65 MB
085 - Create a custom API for inference - Part 2 (Pinehead NotPinehead).mp4
106 MB
086 - Securing SageMaker Notebooks.mp4
113 MB
087 - SageMaker and the VPC.mp4
23 MB
088 - Section Introduction.mp4
10 MB
089 - DeepLens - Part 1.mp4
172 MB
090 - DeepLens - Part 2.mp4
51 MB
091 - DeepRacer - Part 1.mp4
175 MB
092 - DeepRacer - Part 2.mp4
39 MB
093 - How to Answer Questions.mp4
120 MB
094 - How to Prepare.mp4
63 MB
095 - Goodbye!.mp4
40 MB