Transformer models are the de-facto standard in modern NLP. They have proven themselves as the most expressive, powerful models for language by a large margin, beating all major language-based benchmarks time and time again. In this course, we cover everything you need to get started with building cutting-edge performance NLP applications using transformer models like Google AI's BERT, or Facebook AI's DPR. Throughout each of these use-cases we work through a variety of examples to ensure that what, how, and why transformers are so important. Alongside these sections we also work through two full-size NLP projects, one for sentiment analysis of financial Reddit data, and another covering a fully-fledged open domain question-answering application.

In this session, Machine Learning Models for smart water management system which automates the identification of leakage and also predict the location of leakages in the water pipeline will be delivered. Attendees will be able to learn different ML techniques used to predict the leakage in the water pipes and also understand the best approach that can be used to localize the water leakage. The system determines leakages by utilizing the water flow rate in the water pipes The session also highlights the prototype that was developed using STAR-CCM, a computational fluid dynamics software to test the proposed system. Machine Learning models were tested on the prototype developed. The results showed that amongst the machine learning based location prediction models, the Multi-Layer Perceptron (MLP) performs the best with an accuracy of 94.47% and an F1 score of 0.95.

Welcome to the crash course on Numpy, Pandas, Matplotlib by Teaching Bee. In this course we will go through, basics to advance concepts for each library which are prerequisite of data science field. In the first module we will cover important concepts of numpy from basic concepts like difference between numPy array with python list, creating numpy arrays to some advance concepts like Boolean indexing broadcasting etc. In the next section we will be covering concepts of pandas with hands on real world movies dataset and also see various data preprocessing steps which are involved in machine learning using pandas library In the third section we will see how to visualise and interpret data using matplotlib library on real world dataset and also see which type plot is used in different scenarios. As it is said "Practice Makes a Man Perfect", so in last section we will discuss few of the 50 curated exercise questions provided along with course on the above library which we will help you to master these libraries.

If you need to learn how to understand and create Machine Learning models used to solve business problems, this course is for you. You will learn in this course everything you need about Data Mining process, Machine Learning and how to implement Machine Learning algorithms in Data Mining. This course was designed to provide information in a simple and straight forward way so ease learning methods. You will from scratch and keep building your knowledge step by step until you become familiar with the most used Machine Learning algorithms.

If you want to learn all the latest 2019 concepts in applying Deep Learning to Computer Vision, look no further - this is the course for you! You'll get hands the following Deep Learning frameworks in Python:

With artificial intelligence course, you will understand the purpose, codes, and the overall platform of artificial intelligence. It will help you in mastering the essential concept related to python programming and machine learning as well. You will be an expert in writing your python script while performing the high-level mathematical and technical computerized work. Artificial intelligence course program is great enough in terms of giving the training on the skills required for becoming a successful artificial intelligence engineer. The exclusive artificial intelligence online course considers mastering deep learning programming language as well as machine learning.

Apply advanced machine learning models to perform sentiment analysis and classify customer reviews such as Amazon Alexa products reviews Understand the theory and intuition behind several machine learning algorithms such as K-Nearest Neighbors, Support Vector Machines (SVM), Decision Trees, Random Forest, Naive Bayes, and Logistic Regression Implement classification algorithms in Scikit-Learn for K-Nearest Neighbors, Support Vector Machines (SVM), Decision Trees, Random Forest, Naive Bayes, and Logistic Regression Build an e-mail spam classifier using Naive Bayes classification Technique Apply machine learning models to Healthcare applications such as Cancer and Kyphosis diseases classification Develop Models to predict customer behavior towards targeted Facebook Ads Classify data using K-Nearest Neighbors, Support Vector Machines (SVM), Decision Trees, Random Forest, Naive Bayes, and Logistic Regression Build an in-store feature to predict customer's size using their features Develop a fraud detection classifier using Machine Learning Techniques Master Python Seaborn library for statistical plots Understand the difference between Machine Learning, Deep Learning and Artificial Intelligence Perform feature engineering and clean your training and testing data to remove outliers Master Python and Scikit-Learn for Data Science and Machine Learning Learn to use Python Matplotlib library for data Plotting Build an in-store feature to predict customer's size using their features Are you ready to master Machine Learning techniques and Kick-off your career as a Data Scientist?! You came to the right place! Machine Learning skill is one of the top skills to acquire in 2019 with an average salary of over $114,000 in the United States according to PayScale! The total number of ML jobs over the past two years has grown around 600 percent and expected to grow even more by 2020. In this course, we are going to provide students with knowledge of key aspects of state-of-the-art classification techniques.

Deep Learning and Machine Learning are one of the hottest tech fields to be in right now! The field is exploding with opportunities and career prospects. Machine/Deep Learning techniques are widely used in several sectors nowadays such as banking, healthcare, transportation and technology. Machine learning is the study of algorithms that teach computers to learn from experience. Through experience (i.e.: more training data), computers can continuously improve their performance. Deep Learning is a subset of Machine learning that utilizes multi-layer Artificial Neural Networks. Deep Learning is inspired by the human brain and mimics the operation of biological neurons. A hierarchical, deep artificial neural network is formed by connecting multiple artificial neurons in a layered fashion. The more hidden layers added to the network, the more

In this article, we explore the basics of natural language processing (NLP) with code examples. We dive into the natural language toolkit (NLTK) library to present how it can be useful for natural language processing related-tasks. Afterward, we will discuss the basics of other Natural Language Processing libraries and other essential methods for NLP, along with their respective coding sample implementations in Python. Computers and machines are great at working with tabular data or spreadsheets. However, as human beings generally communicate in words and sentences, not in the form of tables. Much information that humans speak or write is unstructured. So it is not very clear for computers to interpret such. In natural language processing (NLP), the goal is to make computers understand the unstructured text and retrieve meaningful pieces of information from it. Natural language Processing (NLP) is a subfield of artificial intelligence, in which its depth involves the interactions between computers and humans.

This course aims to make auto aiming bot at fps games. With the mouse driver we have made, you can give mouse input to all games. I published on udemy all materials used in this course like dataset, scripts, arduino leonardo scripts, trained model. You can follow course easily with use this materials. I did not explain the codes I wrote in this course in detail. It would be helpful to have basic python knowledge. It will be beneficial for you to know how to install programs such as cuda and python on your computer. If you use the techniques in this course, there is a possibility that you will be punished by the game be carefull.