Learn Machine Learning algorithms, softwares, deep learning

Name: Learn Machine Learning algorithms, softwares, deep learning
Rating: 3.7 (618 reviews)

Course covering Deep learning, Neural Networks, KDD, AI, BI, ANN, Decision tree, Bayesian networks, TensorFlow n Knime

Last updated 11/2018

English

What you'll learn

1 section • 5 lectures • 56m total length

3.1 Machine learning introduction7:11
Explore how machine learning learns from data with supervised and unsupervised methods to predict outcomes, build models, and enable tasks like spam filtering and handwriting recognition.
3.2 Machine learning algorithms10:25
Explore machine learning algorithms and deep learning methods, including regression, classification, neural networks, decision trees, clustering, and reinforcement learning, with practical features like SVMs, meta learning, and ensemble approaches.
3.3 Machine learning softwares14:43
Explore a wide range of machine learning software and deep learning frameworks, including CNTK, TensorFlow, Theano, Torch, MXNet, Shogun, Spark, and cloud platforms, for training, deploying, and scaling models.
5.1 AWS and Machine learning7:33
Discover how Amazon Web Services powers machine learning with on‑demand cloud platforms, enabling training and inference on GPU‑optimized instances, S3 storage, and SageMaker managed services.
5.8 TensorFlow - Open source Machine Learning framework16:15
Discover TensorFlow, the open source data-flow framework for machine learning, used in research and production; deploys across desktops, clusters, and mobile, with notebooks and virtual environments for neural networks.

Machine learning course comprises below lectures.

# Course Duration

3.1 Machine learning introduction 00:07:11

3.2 Machine learning algorithms 00:10:25

3.3 Machine learning softwares 00:14:43

5.1 AWS and Machine learning 00:08:51

5.8 TensorFlow - Open source Machine Learning framework 00:16:15

Machine Learning on AWS covers more details about concepts of TensorFlow, Amazon SageMaker and other AWS ML topics.

Course covering KDD, AI, BI, Deep learning, Neural Networks, ANN, Decision tree, Bayesian networks, TensorFlow and Knime

For all those who is interested in learning about Machine Learning and Data science.