ACloudGuru | AWS Certified Machine Learning – Specialty 2019 [FCO...

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Ace the AWS Machine Learning Specialty Certification exam with ACG – no PhD in Mathematics needed!

78 TOTAL LESSONS
13 HOURS OF VIDEO

01 — ABOUT THE COURSE

Scott Pletcher – Hello Cloud Gurus,

Your executive board members are asking you to do something with it. Your grandmother is asking you if it will put you out of a job. Your deadbeat college roommate is asking if you can help him find a date with it. Everyone seems to fuss over Machine Learning, but how many of us truly understand it? Too few.

Fortunately, ACG has your back yet again with a fresh course focused on helping you outsmart the new AWS Certified Machine Learning Specialty. In typical ACG manner, we have created a course that confronts the potentially dull and boring topic of machine learning head-on with quirky and engaging lectures, interactive labs and plenty of real-world, plain-speak examples.

In this course, you’ll learn :

• The domains of knowledge for the AWS Certified Machine Learning Speciality exam.
• Best practices for using the tools and platforms of AWS for data engineering, data analysis, machine learning modeling, model evaluation and deployment.
• Hands-on labs designed to challenge your intuition, creativity and knowledge of the AWS platform.

With this course you’ll get a solid understanding of the services and platforms available on AWS for Machine Learning projects, build a foundation to pass the certification exam and feel equipped to use the AWS ML portfolio in your own real-world applications.

Don’t just sit idly by, watching as robotic overlords take over the world. Create your own army of sentient machines and beat them at their own game! And keep being awesome, cloud gurus!



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01 Introduction
  • 001 Course Introduction.mp4 (27.7 MB)
  • 002 About The Exam.mp4 (62.0 MB)
  • 002 Exam Blueprint.pdf (543.2 KB)
  • 003 About This Course.mp4 (84.4 MB)
02 Data Collection
  • 001 Introduction.mp4 (18.4 MB)
  • 002 Concepts.mp4 (37.1 MB)
  • 003 General Data Terminology.mp4 (30.3 MB)
  • 004 Image Net Data.txt (0.0 KB)
  • 004 MNIST Data.txt (0.0 KB)
  • 004 Machine Learning Data Terminology.mp4 (57.2 MB)
  • 004 Technobabble.txt (0.0 KB)
  • 004 Turboencabulator Video.txt (0.0 KB)
  • 005 AWS Data Stores.mp4 (23.6 MB)
  • 006 AWS Glue Classifiers.html (40.3 KB)
  • 006 AWS Migration Tools.mp4 (27.8 MB)
  • 006 DMS Release Review.txt (0.0 KB)
  • 006 Data Pipeline Activities.html (15.6 KB)
  • 007 AWS Helper Tools.mp4 (12.2 MB)
  • 008 AWS reInvent 2018 Effective Data Lakes Challenges and Design Patterns.txt (0.0 KB)
  • 008 AWS reInvent 2018 Modern Cloud Data Warehousing.txt (0.0 KB)
  • 008 Build a Data Lake Foundation with AWS Glue and Amazon S3.txt (0.1 KB)
  • 008 Exam Tips.mp4 (15.0 MB)
  • 008 Whitepaper - AWS Database Migration Service Best Practices.pdf (583.4 KB)
  • 008 Whitepaper - Big Data Aanlytics Options on AWS.pdf (757.2 KB)
  • 008 Whitepaper - Data Warehousing on AWS.pdf (350.7 KB)
  • 008 Whitepaper - Migrating to Apache HBase on Amazon S3 on Amazon EMR.pdf (809.5 KB)
  • 008 Whitepaper - Sizing Cloud Data Warehouses.pdf (367.9 KB)
03 Streaming Data Collection
  • 001 Introduction.mp4 (4.3 MB)
  • 002 AWS Open Data Registry.txt (0.0 KB)
  • 002 Concepts.mp4 (33.4 MB)
  • 002 Googles Big Query.txt (0.0 KB)
  • 002 Kaggle.txt (0.0 KB)
  • 002 UCI Machine Learning Repository.txt (0.0 KB)
  • 003 AWS reInvent 2018 High Performance Data Streaming with Amazon Kinesis Best Practices.txt (0.0 KB)
  • 003 Kinesis Data Streams Key Concepts.html (27.9 KB)
  • 003 Kinesis Data Streams.mp4 (45.6 MB)
  • 004 Kinesis Firehose.mp4 (16.6 MB)
  • 004 Streaming ETL for Data Lakes using Amazon Kinesis Firehose.txt (0.0 KB)
  • 004 What Is Amazon Kinesis Data Firehose.html (22.8 KB)
  • 005 Analyze live video at scale in real time using Amazon Kinesis Video Streams and Amazon SageMaker.txt (0.1 KB)
  • 005 Deep Dive - Amazon Kinesis Video Streams.txt (0.0 KB)
  • 005 Kinesis Video Streams.mp4 (11.8 MB)
  • 006 Analyzing Data Streams in Real Time with Amazon Kinesis.txt (0.0 KB)
  • 006 Create real-time clickstream sessions and run analytics with Amazon Kinesis Data Analytics AWS Glue and Amazon Athena.txt (0.2 KB)
  • 006 Joining and Enriching Streaming Data on Amazon Kinesis.txt (0.1 KB)
  • 006 Kinesis Data Analytics.mp4 (21.5 MB)
  • 007 Exam Tips.mp4 (6.8 MB)
  • 007 Real-Time Machine Learning Using Amazon Kinesis.txt (0.0 KB)
  • 007 WHITEPAPER - Streaming Data Solutions on AWS with Amazon Kinesis.pdf (1.1 MB)
  • 008 CloudFormation Template (setup data producer).txt (0.1 KB)
  • 008 Create Subset Transformation Query.txt (0.1 KB)
  • 008 Lambda function (add-newline-function).txt (0.1 KB)
  • 008 PutRecord Python program.py (0.1 KB)
  • 008 Streaming Data Collection Lab.mp4 (125.5 MB)
  • 008 httpsrandomuser.txt (0.0 KB)
04 Data Preparation
  • 001 Introduction.mp4 (4.7 MB)
  • 002 Concepts.mp4 (21.6 MB)
  • 003 Categorical Encoding.mp4 (32.8 MB)
  • 004 Text Feature Engineering.mp4 (58.5 MB)
  • 004 tf-idf Vectorizer.html (48.5 KB)
  • 005 Numeric Feature Engineering.mp4 (23.7 MB)
  • 005 scikit-learn MinMaxScaler (Normalization).html (33.5 KB)
  • 005 scikit-learn StandardScaler (Standardization).html (43.5 KB)
  • 006 Common Dataset Formats.html (31.0 KB)
  • 006 MNIST datasets.txt (0.0 KB)
  • 006 Other Feature Engineering.mp4 (27.0 MB)
  • 007 Handling Missing Values.mp4 (15.3 MB)
  • 008 Feature Selection.mp4 (11.3 MB)
  • 009 AWS Glue - How it works.html (21.2 KB)
  • 009 AWS Glue Release Review.txt (0.0 KB)
  • 009 AWS reInvent 2018 Integrate Amazon SageMaker with Apache Spark.txt (0.0 KB)
  • 009 Getting Started with AWS Glue ETL.txt (0.0 KB)
  • 009 Helper Tools.mp4 (53.4 MB)
  • 009 Using Apache Spark with Amazon SageMaker - AWS Online Tech Talks.txt (0.0 KB)
  • 009 What is AWS Glue.txt (0.0 KB)
  • 010 AWS reInvent 2018 Building Serverless Analytics Pipelines with AWS Glue.txt (0.0 KB)
  • 010 AWS reInvent 2018 Integrate Amazon SageMaker with Apache Spark.txt (0.1 KB)
  • 010 Build a Data Lake Foundation with AWS Glue and Amazon S3.txt (0.1 KB)
  • 010 Building Serverless ETL Pipelines with AWS Glue.txt (0.0 KB)
  • 010 Exam Tips.mp4 (26.9 MB)
  • 011 Age Groupings Query.txt (0.1 KB)
  • 011 Data Preparation Lab.mp4 (104.0 MB)
  • 011 Gender Percentages Query.txt (0.1 KB)
  • 011 Gender mapping pyspark code.py (0.1 KB)
  • 011 Most Common Ages Query.txt (0.0 KB)
  • 011 User Data (user-data).txt (0.1 KB)
05 Data Analysis and Visualization
  • 001 Introduction.mp4 (9.8 MB)
  • 002 Concepts.mp4 (16.7 MB)
  • 002 Gapminder Tool.txt (0.0 KB)
  • 003 Relationships.mp4 (20.1 MB)
  • 004 Comparisons.mp4 (13.3 MB)
  • 005 Distributions.mp4 (19.5 MB)
  • 006 Compositions.mp4 (9.6 MB)
  • 007 Choosing A Visualization.mp4 (21.0 MB)
  • 008 AWS reInvent 2018 Introducing ML Insights with Amazon QuickSight.txt (0.0 KB)
  • 008 Amazon QuickSight Announces General Availability of ML Insights.txt (0.1 KB)
  • 008 Exam Tips.mp4 (7.7 MB)
  • 008 Matplotlib Python Library.txt (0.0 KB)
  • 009 Box Plot Jupyter Notebook (box-plot-example.txt (0.1 KB)
  • 009 Car Dataset (car_data.txt (0.1 KB)
  • 009 Data Analysis and Visualization Lab.mp4 (149.9 MB)
  • 009 Jupyter Notebooks.txt (0.0 KB)
  • 009 my-manifest.json (0.1 KB)
06 Modeling
  • 001 Introduction.mp4 (2.8 MB)
  • 002 Concepts.mp4 (37.1 MB)
  • 003 Data Preparation.mp4 (27.1 MB)
  • 004 SageMaker Modeling.mp4 (48.8 MB)
  • 005 SageMaker Training.mp4 (39.0 MB)
  • 006 Amazon Machine Learning Key Concepts.html (49.9 KB)
  • 006 Exam Tips.mp4 (9.3 MB)
  • 006 Managing Machine Learning Projects.pdf (747.2 KB)
  • 006 Use Your Own Algorithms with Amazon SageMaker.html (28.9 KB)
  • 007 Jupyter Notebook (ufo-modeling-lab.txt (0.1 KB)
  • 007 K-Means Hyperparameters Documentation.html (29.2 KB)
  • 007 K-Means SageMaker Documentation.html (59.3 KB)
  • 007 Modeling Lab.mp4 (144.0 MB)
  • 007 UFO Sightings Dataset (ufo_fullset.txt (0.1 KB)
07 Algorithms
  • 001 Introduction.mp4 (2.5 MB)
  • 002 OPTIONAL - Why do we call them Algorithms.mp4 (49.7 MB)
  • 003 Concepts.mp4 (47.3 MB)
  • 004 Regression.mp4 (46.2 MB)
  • 005 Clustering.mp4 (24.9 MB)
  • 006 Classification.mp4 (23.6 MB)
  • 007 Image Analysis.mp4 (27.5 MB)
  • 008 Anomaly Detection.mp4 (20.3 MB)
  • 009 Text Analytics.mp4 (32.8 MB)
  • 010 Reinforcement Learning.mp4 (29.4 MB)
  • 011 Forecasting.mp4 (17.0 MB)
  • 012 Ensemble Learning.mp4 (24.1 MB)
  • 013 Exam Tips.mp4 (21.5 MB)
  • 013 Use Amazon SageMaker Built-in Algorithms.html (30.3 KB)
  • 014 Algorithms Lab.mp4 (196.0 MB)
  • 014 Jupyter Notebook (ufo-algorithms-lab.txt (0.1 KB)
  • 014 UFO Sightings Dataset (ufo_fullset.txt (0.1 KB)
08 Evaluation and Optimization
  • 001 Introduction.mp4 (1.6 MB)
  • 002 Concepts.mp4 (19.2 MB)
  • 003 Monitoring and Analyzing Training Jobs.mp4 (11.1 MB)
  • 004 Evaluating Model Accuracy.mp4 (45.0 MB)
  • 005 Model Tuning.mp4 (24.7 MB)
  • 006 Amazon SageMaker Automatic Model Tuning Using Machine Learning for Machine Learning.txt (0.1 KB)
  • 006 Easily monitor and visualize metrics while training models on Amazon SageMaker.txt (0.1 KB)
  • 006 Exam Tips.mp4 (10.4 MB)
  • 006 Incremental Training in Amazon SageMaker.html (46.6 KB)
  • 007 Evaluation and Optimization Lab.mp4 (164.3 MB)
  • 007 Hyperparameter Tuning with Amazon SageMakers Automatic Model Tuning - AWS Online Tech Talks.txt (0.0 KB)
  • 007 Jupyter Notebook (ufo-evaluation-optimization-lab.txt (0.1 KB)
  • 007 Linear Learner Hyperparameters.html (76.1 KB)
  • 007 Training Dataset in recordIO Protobuf format (ufo_sightings_train_recordIO_protobuf.txt (0.1 KB)
  • 007 Validation Dataset in recordIO Protobuf format (ufo_sightings_validation_recordIO_protobuf.txt (0.1 KB)
09 Implementation and Operations
  • 001 Introduction.mp4 (2.2 MB)
  • 002 Concepts.mp4 (43.1 MB)
  • 003 AI Developer Services.mp4 (17.7 MB)
  • 004 Amazon SageMaker Deployments.mp4 (36.3 MB)
  • 005 Other ML Deployment Options.mp4 (7.3 MB)
  • 006 Security.mp4 (43.6 MB)
  • 007 Monitor and Evaluate.mp4 (34.3 MB)
  • 008 Exam Tips.mp4 (14.1 MB)
  • 009 Call an Amazon SageMaker model endpoint using Amazon API Gateway and AWS Lambda.txt (0.1 KB)
  • 009 Implementation and Operations Lab.mp4 (164.1 MB)
  • 009 Jupyter Notebook (ufo-implementation-operations-lab.txt (0.1 KB)
  • 009 Lambda Function (lambda_function.py (0.1 KB)
  • 009 Sample Request JSON (sample_request.json (0.1 KB)
  • 009 UFO Full Dataset (ufo_fullset.txt (0.1 KB)
  • 010 Deconstruction Lab.mp4 (11.1 MB)
10 Wrap-Up
  • 001 Good Luck.mp4 (8.2 MB)

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