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Data Science & Machine Learning Master's program

Data Science & Machine Learning Master's program online training you will master..

  • 50000 45000
What you will learn
  • Perform scientific & technical computing using SciPy package & its sub-packages such as Integrate, Optimize, Statistics,...
  • In-depth understanding of supervised & unsupervised learning models like linear & logistic regression, clustering, dimen...
  • Learn how to implement the unsupervised learning algorithms, including deep learning, clustering, & recommendation syste...
  • Develop an understanding classification data and models
  • Gain important experiences into signs, pictures, and sounds with SciPy, scikit-picture, and OpenCV
  • Analyze information with Bayesian or frequentist insights (Pandas, PyMC, & R), & gain from genuine information through A...
Machine Learning with R

Machine Learning with R online training course covers a detailed overview of va..

  • 45000 40000
What you will learn
  • Develop an understanding of categorical variables and continuous variables, that helps in using the boosting and bagging...
  • Understand kernel functions such as: spline kernels, linear, radial basis function and polynomial and Text Mining with R...
  • Explore R language fundamentals, including basic syntax, variables, and types
  • Why Support Vector Machines is called the most high-performing algorithm
  • How neural networks effective in image segmentation. How to use the calculus in simpler form
Machine Learning Master Program

Our Machine learning Master's Program online training course includes training..

  • 40000 35000
What you will learn
  • Understand how to make an accurate predictions
  • Learn how to deal with the advanced techniques like Dimensionality Reduction
  • Develop an understanding on the issues of specific topics like Reinforcement Learning, NLP and Deep Learning & how to ha...
  • Develop understanding of many of the Machine Learning models
  • Develop understanding on all the essentials such as: Data Preprocessing, Regression, Classification, Clustering, Associa...
  • Determine the various applications of machine learning algorithms
  • Learn the how to implement the unsupervised learning algorithms, which includes deep learning, clustering, and recommen...
AWS Certified Machine Learning – Specialty (MLS-C0...

This AWS Certified Machine Learning training course is specifically designed to..

  • 35000 30000
What you will learn
  • Amazon SageMaker's built-in machine learning algorithms (XGBoost, BlazingText, Object Detection, etc.)
  • Feature engineering techniques, including imputation, outliers, binning, and normalization
  • High-level ML services: Comprehend, Translate, Polly, Transcribe, Lex, Rekognition, and more
  • Data engineering with S3, Glue, Kinesis, and DynamoDB
  • Exploratory data analysis with scikit_learn, Athena, Apache Spark, and EMR
  • Deep learning and hyperparameter tuning of deep neural networks
  • Automatic model tuning and operations with SageMaker
  • L1 and L2 regularization
  • Applying security best practices to machine learning pipeline

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What you will learn
  • Perform scientific & technical computing using SciPy package & its sub-packages such as Integrate, Optimize, Statistics,...
  • In-depth understanding of supervised & unsupervised learning models like linear & logistic regression, clustering, dimen...
  • Learn how to implement the unsupervised learning algorithms, including deep learning, clustering, & recommendation syste...
  • Develop an understanding classification data and models
  • Gain important experiences into signs, pictures, and sounds with SciPy, scikit-picture, and OpenCV
  • Analyze information with Bayesian or frequentist insights (Pandas, PyMC, & R), & gain from genuine information through A...
What you will learn
  • Develop an understanding of categorical variables and continuous variables, that helps in using the boosting and bagging...
  • Understand kernel functions such as: spline kernels, linear, radial basis function and polynomial and Text Mining with R...
  • Explore R language fundamentals, including basic syntax, variables, and types
  • Why Support Vector Machines is called the most high-performing algorithm
  • How neural networks effective in image segmentation. How to use the calculus in simpler form
What you will learn
  • Understand how to make an accurate predictions
  • Learn how to deal with the advanced techniques like Dimensionality Reduction
  • Develop an understanding on the issues of specific topics like Reinforcement Learning, NLP and Deep Learning & how to ha...
  • Develop understanding of many of the Machine Learning models
  • Develop understanding on all the essentials such as: Data Preprocessing, Regression, Classification, Clustering, Associa...
  • Determine the various applications of machine learning algorithms
  • Learn the how to implement the unsupervised learning algorithms, which includes deep learning, clustering, and recommen...
What you will learn
  • Amazon SageMaker's built-in machine learning algorithms (XGBoost, BlazingText, Object Detection, etc.)
  • Feature engineering techniques, including imputation, outliers, binning, and normalization
  • High-level ML services: Comprehend, Translate, Polly, Transcribe, Lex, Rekognition, and more
  • Data engineering with S3, Glue, Kinesis, and DynamoDB
  • Exploratory data analysis with scikit_learn, Athena, Apache Spark, and EMR
  • Deep learning and hyperparameter tuning of deep neural networks
  • Automatic model tuning and operations with SageMaker
  • L1 and L2 regularization
  • Applying security best practices to machine learning pipeline
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