Welcome to the first advanced and project-based Pandas Data Science Course! No matter if you need excellent Pandas skills for Data Analysis, Machine Learning or Finance purposes, this is the right Course for you to get your skills to Expert Level! Efficiently import and merge Data from many text/CSV files. Clean, handle and flatten nested and stringified Data in DataFrames. Know how to handle and normalize Unicode strings.

Intel is working to improve workloads for artificial intelligence (AI) developers and data scientists by offering a wide variety of AI Python optimizations and tools. Whether you are at the beginning of your AI journey and looking to learn more, or you consider yourself a data science veteran, you can find great insight about Intel's tools and technology offerings through this showcase and the accompanying resources. This Tech Field Day Showcase is presented by Todd Tomashek, Software Engineering Manager in Machine Learning Performance at Intel. Chris Grundemann is a passionate, creative technologist and a strong believer in technology's power to aid in the betterment of humankind. In his current role as Managing Director at Grundemann Technology Solutions he is expressing that passion by helping technology businesses grow and by helping any business grow with technology.

Free Coupon Discount - TensorFlow 2.0 Practical Advanced, Master Tensorflow 2.0, Google's most powerful Machine Learning Library, with 5 advanced practical projects Created by Dr. Ryan Ahmed, Ph.D., MBA, Kirill Eremenko, Hadelin de Ponteves, SuperDataScience Team, Mitchell Bouchard Students also bought Recommender Systems and Deep Learning in Python Machine Learning and AI: Support Vector Machines in Python Natural Language Processing with Deep Learning in Python Artificial Intelligence: Reinforcement Learning in Python Data Science: Deep Learning in Python Preview this Udemy Course GET COUPON CODE Description Google has recently released TensorFlow 2.0 which is Google's most powerful open source platform to build and deploy AI models in practice. Tensorflow 2.0 release is a huge win for AI developers and enthusiast since it enabled the development of super advanced AI techniques in a much easier and faster way. The purpose of this course is to provide students with practical knowledge of building, training, testing and deploying Advanced Artificial Neural Networks and Deep Learning models using TensorFlow 2.0 and Google Colab. This course will cover advanced, state-of-the–art AI models implementation in TensorFlow 2.0 such as DeepDream, AutoEncoders, Generative Adversarial Networks (GANs), Transfer Learning using TensorFlow Hub, Long Short Term Memory (LSTM) Recurrent Neural Networks and many more. The applications of these advanced AI models are endless including new realistic human photographs generation, text translation, image de-noising, image compression, text-to-image translation, image segmentation, and image captioning.

Are you ready to start your path to becoming a Data Scientist! Data is at the heart of our digital economy and data science has been ranked as the hottest profession of the 21st century. Whether you are new to the job market or already in the workforce and looking to upskill yourself, this five course Data Science with Python Professional Certificate program is aimed at preparing you for a career in data science and machine learning. No prior computer programming experience required! You will start by learning Python, the most popular language for data science.

You'll start by absorbing the most valuable PyTorch basics and techniques. I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts. My course will help you implement the methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement Python-based data science in real -life. After taking this course, you'll easily use packages like Numpy, Pandas, and PIL to work with real data in Python along with gaining fluency in PyTorch.

Description 2021 Python for Machine Learning & Data Science Masterclass is the name of a training course in which data science and machine learning using Python are discussed. This course includes Numpy, Pandas, Matplotlib and Scikit-Learn training. This is one of the most complete courses in data science and machine learning on the Internet. After teaching more than 2 million learners, the instructor of this course has collected items over a year that he believes is the best way to teach zero. This comprehensive course is designed to be at the bootcamps level, which usually costs thousands of dollars.

Udemy Coupon - Solve Real World Business Problems with AI Solutions Created by Hadelin de Ponteves, Kirill Eremenko, SuperDataScience Team English [Auto-generated], French [Auto-generated], 5 more Students also bought Artificial Intelligence: Reinforcement Learning in Python Data Science: Natural Language Processing (NLP) in Python Recommender Systems and Deep Learning in Python Cluster Analysis and Unsupervised Machine Learning in Python Natural Language Processing with Deep Learning in Python Preview this Course GET COUPON CODE Description Structure of the course: Part 1 - Optimizing Business Processes Case Study: Optimizing the Flows in an E-Commerce Warehouse AI Solution: Q-Learning Part 2 - Minimizing Costs Case Study: Minimizing the Costs in Energy Consumption of a Data Center AI Solution: Deep Q-Learning Part 3 - Maximizing Revenues Case Study: Maximizing Revenue of an Online Retail Business AI Solution: Thompson Sampling Real World Business Applications: With Artificial Intelligence, you can do three main things for any business: Optimize Business Processes Minimize Costs Maximize Revenues We will show you exactly how to succeed these applications, through Real World Business case studies. And for each of these applications we will build a separate AI to solve the challenge. In Part 1 - Optimizing Processes, we will build an AI that will optimize the flows in an E-Commerce warehouse. In Part 2 - Minimizing Costs, we will build a more advanced AI that will minimize the costs in energy consumption of a data center by more than 50%! Just as Google did last year thanks to DeepMind.

Description HERE IS WHY YOU SHOULD TAKE THIS COURSE: This course your complete guide to both supervised & unsupervised learning using Python. This means, this course covers all the main aspects of practical data science and if you take this course, you can do away with taking other courses or buying books on Python based data science. In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal.. By becoming proficient in unsupervised & supervised learning in Python, you can give your company a competitive edge and boost your career to the next level. LEARN FROM AN EXPERT DATA SCIENTIST WITH 5 YEARS OF EXPERIENCE: My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate.

Free Coupon Discount - Advanced AI: Deep Reinforcement Learning in Python The Complete Guide to Mastering Artificial Intelligence using Deep Learning and Neural Networks | Created by Lazy Programmer Team, Lazy Programmer Inc. Students also bought Artificial Intelligence: Reinforcement Learning in Python Data Science: Natural Language Processing (NLP) in Python Unsupervised Machine Learning Hidden Markov Models in Python Cluster Analysis and Unsupervised Machine Learning in Python Complete Python Bootcamp: Go from zero to hero in Python 3 Preview this Udemy Course GET COUPON CODE 100% Off Udemy Coupon . Free Udemy Courses . Online Classes

These topics are getting very hot nowadays because these learning algorithms can be used in several fields from software engineering to investment banking. Learning algorithms can recognize patterns which can help detect cancer for example or we may construct algorithms that can have a very good guess about stock prices movement in the market. In each section we will talk about the theoretical background for all of these algorithms then we are going to implement these problems together. We will use Python with SkLearn, Keras and TensorFlow. Machine Learning Algorithms: machine learning approaches are becoming more and more important even in 2020.