Free Coupon Discount - Machine Learning & Deep Learning in Python & R, Covers Regression, Decision Trees, SVM, Neural Networks, CNN, Time Series Forecasting and more using both Python & R Hot & New Created by Start-Tech Academy English [Auto] Preview this Udemy Course - GET COUPON CODE 100% Off Udemy Coupon . Free Udemy Courses . Online Classes
Do you want to make your career in Data Science? Want to have a successful career and a life worth inspiring? All you need is the will to succeed and the passion to learn!!! Python being one of the most widely used languages is the new mantra for success. It is the number one tool for analytical professionals and is one of the top programming languages in the year 2019. Our aim is to make the students get acquainted with python and become proficient in the most popular programming language.
The Artificial Intelligence and Deep Learning are growing exponentially in today's world. There are multiple application of AI and Deep Learning like Self Driving Cars, Chat-bots, Image Recognition, Virtual Assistance, ALEXA, so on... With this course you will understand the complexities of Deep Learning in easy way, as well as you will have A Complete Understanding of Googles TensorFlow 2.0 Framework TensorFlow 2.0 Framework has amazing features that simplify the Model Development, Maintenance, Processes and Performance In TensorFlow 2.0 you can start the coding with Zero Installation, whether you're an expert or a beginner, in this course you will learn an end-to-end implementation of Deep Learning Algorithms So what are you waiting for, Enroll Now and understand Deep Learning to advance your career and increase your knowledge!
This course is all about the application of deep learning and neural networks to reinforcement learning. If you've taken my first reinforcement learning class, then you know that reinforcement learning is on the bleeding edge of what we can do with AI. Specifically, the combination of deep learning with reinforcement learning has led to AlphaGo beating a world champion in the strategy game Go, it has led to self-driving cars, and it has led to machines that can play video games at a superhuman level. Reinforcement learning has been around since the 70s but none of this has been possible until now. The world is changing at a very fast pace.
This course focuses on using state-of-the-art Natural Language processing techniques to solve the problem of question generation in edtech. If we pick up any middle school textbook, at the end of every chapter we see assessment questions like MCQs, True/False questions, Fill-in-the-blanks, Match the following, etc. In this course, we will see how we can take any text content and generate these assessment questions using NLP techniques. This course will be a very practical use case of NLP where we put basic algorithms like word vectors (word2vec, Glove, etc) to recent advancements like BERT, openAI GPT-2, and T5 transformers to real-world use. We will use NLP libraries like Spacy, NLTK, AllenNLP, HuggingFace transformers, etc.
Published Tuesday, May. 4, 2021, 9:11 am With tremendous data being generated every second, it is not difficult to imagine the potential of the many vital insights hiding in the data. Today, organizations focus on analyzing this collected data to discover insights into crucial business-related questions: How did the sales perform against estimated target sales in the last quarter? Are older customers contributing more to sales? Which customers should be given coupons? Let us understand how data science is helping organizations answer questions like these.
Artificial Intelligence (AI) has arguably become a household term in modern enterprises. By now, most companies have embraced some type of business initiative that includes AI in their digital transformation. Artificial Intelligence is a broad term, but much current research and development focuses on machine learning (ML), a subdiscipline whereby machines learn from data as opposed to being explicitly programmed. With AI and ML targeting a broad spectrum of enterprise users, IT professionals must develop new skills to succeed in this emerging space. An understanding of the business and its most pressing problems is a transcendent competency for any IT professional.
Learn advanced machine learning techniques and algorithms and how to package and deploy your models to a production environment. Gain practical experience using Amazon SageMaker to deploy trained models to a web application and evaluate the performance of your models. A/B test models and learn how to update the models as you gather more data, an important skill in industry. This program is intended for students who already have knowledge of machine learning algorithms. Learn advanced machine learning deployment techniques and software engineering best practices.
What is the difference between the Data Analyst, Machine Learning Engineer, and the Data Scientist Nanodegree programs? The Data Analyst program is designed for people with some data analysis experience and little-to-no programming experience. Students will learn to analyze data using Python and SQL, to wrangle and clean messy data, to use applied statistics to test hypotheses, and to create data visualizations. Graduates of this program will be prepared for data analyst positions. The Data Scientist Nanodegree program is designed for students with strong programming and data analysis skills, as it is the next step for graduates of the Data Analyst Nanodegree program.