Learn Python, NumPy, Pandas, Scikit-learn, Spark, Hadoop, Regression, Classification, SVM, ANN, Business Analytics and More
Learn Python, NumPy, Pandas, Scikit-learn, TensorFlow 2.0, Keras, Regression, Classification, SVM, Decision Trees, Random Forests, Ensemble Learning, Dimensionality Reduction, Unsupervised Learning, Convolutional and Recurrent Neural Networks, Natural Language Processing, Autoencoders, Generative Adversarial Networks, Reinforcement Learning and More
Learn to design a machine learning system end-to-end. Build expertise in training, deploying, scaling and monitoring the performance of your machine learning model in production.
Learn DevOps Tools - Linux, Git, Docker, Kubernetes, Ansible, Terraform, Jenkins, and Graffana. Training will cover all the stages of the software development lifecycle.
Learn Deep Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Autoencoders, and Reinforcement Learning
Learn Python, NumPy, Pandas, Scikit-learn, HDFS, ZooKeeper, Hive, HBase, NoSQL, Oozie, Flume, Sqoop, Spark, Spark RDD, Spark Streaming, Kafka, SparkR, SparkSQL, MLlib, Regression, Clustering, Classification, SVM, Random Forests, Decision Trees, Dimensionality Reduction, TensorFlow 2, Keras, Convolutional & Recurrent Neural Networks, Autoencoders, and Reinforcement Learning
Learn HDFS, ZooKeeper, Hive, HBase, NoSQL, Oozie, Flume, Sqoop, Spark, Spark RDD, Spark Streaming, Kafka, SparkR, SparkSQL, MLlib, and GraphX.
Learn how to boost deep learning algorithms on various processor platforms and custom accelerators; and how to make them more secure and reliable.
Learn Python, NumPy, Pandas, scikit-learn, Regression, Clustering, Classification, SVM, Random Forests, Decision Trees, Dimensionality Reduction, TensorFlow 2, Keras, Convolutional & Recurrent Neural Networks, Autoencoders, and Reinforcement Learning
Learn Python, Artificial Neural Networks, TensorFlow 2, Convolutional & Recurrent Neural Networks, and Natural Language Processing
Learn Open CV, Python, Artificial Neural Networks, TensorFlow 2, Convolutional & Recurrent Neural Networks, Autoencoders and Reinforcement Learning
Learn Python, NumPy, Scipy, Pandas, Jupyter, Scikit-learn, Regression, Clustering, Classification, Support Vector Machines, Random Forests, Decision Trees and Dimensionality Reduction
