GCP Machine Learning Eng. PRO |
この情報はストアのものより古い可能性がございます。 | ||||
価格 | 2000円 | ダウンロード |
||
---|---|---|---|---|
ジャンル | 教育 | |||
サイズ | 8.2MB | |||
開発者 | DjamgaTech Corp | |||
順位 |
| |||
リリース日 | 2022-03-03 17:00:00 | 評価 | 評価が取得できませんでした。 | |
互換性 | iOS 11.0以降が必要です。 iPhone、iPad および iPod touch 対応。 |
Use this App to learn about Machine Learning on GCP and prepare for the GCP Professional Machine Learning Engineer.
Earning Google GCP Professional Machine Learning Engineer validates expertise in building, training, tuning, and deploying machine learning (ML) models on GCP.
The App provides hundreds of quizzes and practice exams about:
- Machine Learning Operation on GCP
- Framing ML problems,
- Architecting ML solutions,
- Designing data preparation and processing systems,
- Developing ML models,
- Modelling
- Data Engineering
- Computer Vision,
- Exploratory Data Analysis,
- ML implementation & Operations
- Machine Learning Basics Questions and Answers
- Machine Learning Advanced Questions and Answers
- Scorecard
- Countdown timer
- Machine Learning Cheat Sheets
- Machine Learning Interview Questions and Answers
- Machine Learning Latest News
- No ADS
The App covers Machine Learning Basics and Advanced topics including: Monitoring, optimizing, and maintaining ML solutions, Automating and orchestrating ML pipelines, NLP, Modelling, Data Engineering, Computer Vision, Exploratory Data Analysis, ML implementation and Operations, Cloud Build, Kubeflow, TensorFlow, CSV, JSON, IMG, parquet or databases, Hadoop/Spark, Vertex AI Prediction, containerized serving, Kubeflow Pipelines/Vertex AI Pipelines, Cloud Composer/Apache Airflow,evaluation of drift or bias, NLP, Computer Vision, Python, linear regression, logistic regression, Sampling, dataset, statistical interaction, selection bias, non-Gaussian distribution, bias-variance trade-off, Normal Distribution, correlation and covariance, Point Estimates and Confidence Interval, A/B Testing, p-value, statistical power of sensitivity, over-fitting and under-fitting, regularization, Law of Large Numbers, Confounding Variables, Survivorship Bias, univariate, bivariate and multivariate, Resampling, ROC curve, TF/IDF vectorization, Cluster Sampling, etc.
Important: To succeed with the real exam, do not memorize the answers in this app. It is very important that you understand why a question is right or wrong and the concepts behind it by carefully reading the reference documents in the answers.
Note and disclaimer: We are not affiliated with Microsoft or Azure or Google or Amazon. The questions are put together based on the certification study guide and materials available online. The questions in this app should help you pass the exam but it is not guaranteed. We are not responsible for any exam you did not pass.
Earning Google GCP Professional Machine Learning Engineer validates expertise in building, training, tuning, and deploying machine learning (ML) models on GCP.
The App provides hundreds of quizzes and practice exams about:
- Machine Learning Operation on GCP
- Framing ML problems,
- Architecting ML solutions,
- Designing data preparation and processing systems,
- Developing ML models,
- Modelling
- Data Engineering
- Computer Vision,
- Exploratory Data Analysis,
- ML implementation & Operations
- Machine Learning Basics Questions and Answers
- Machine Learning Advanced Questions and Answers
- Scorecard
- Countdown timer
- Machine Learning Cheat Sheets
- Machine Learning Interview Questions and Answers
- Machine Learning Latest News
- No ADS
The App covers Machine Learning Basics and Advanced topics including: Monitoring, optimizing, and maintaining ML solutions, Automating and orchestrating ML pipelines, NLP, Modelling, Data Engineering, Computer Vision, Exploratory Data Analysis, ML implementation and Operations, Cloud Build, Kubeflow, TensorFlow, CSV, JSON, IMG, parquet or databases, Hadoop/Spark, Vertex AI Prediction, containerized serving, Kubeflow Pipelines/Vertex AI Pipelines, Cloud Composer/Apache Airflow,evaluation of drift or bias, NLP, Computer Vision, Python, linear regression, logistic regression, Sampling, dataset, statistical interaction, selection bias, non-Gaussian distribution, bias-variance trade-off, Normal Distribution, correlation and covariance, Point Estimates and Confidence Interval, A/B Testing, p-value, statistical power of sensitivity, over-fitting and under-fitting, regularization, Law of Large Numbers, Confounding Variables, Survivorship Bias, univariate, bivariate and multivariate, Resampling, ROC curve, TF/IDF vectorization, Cluster Sampling, etc.
Important: To succeed with the real exam, do not memorize the answers in this app. It is very important that you understand why a question is right or wrong and the concepts behind it by carefully reading the reference documents in the answers.
Note and disclaimer: We are not affiliated with Microsoft or Azure or Google or Amazon. The questions are put together based on the certification study guide and materials available online. The questions in this app should help you pass the exam but it is not guaranteed. We are not responsible for any exam you did not pass.
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