***** Python Certification Training for Data Science: https://www.edureka.co/data-science-python-certification-course ***** This Edureka live session will introduce you to the top 10 most trending Python libraries. The 10 python libraries included in this session are: 1. TensorFlow 2. Scikit-learn 3. SciPy 4. NumPy 5. Pandas 6. Selenium 7. PySpark 8. OpenCV 9. Matplotlib 10. Django Subscribe to our channel to get video updates. Hit the subscribe button above. For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka – – – – – – – – – – – – – – – – – About the Course Edureka’s Python Data Science course is designed to make you grab the concepts of Machine Learning. The course will provide deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in python programming language. Furthermore, you will be taught of Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real life scenarios using Machine Learning Algorithms. Towards the end of the course we will be discussing various practical use cases of Machine Learning in python programming language to enhance your learning experience. – – – – – – – – – – – – – – – – – – – Why learn Data Science? Data Science is a set of techniques that enables the computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning.