Instructional Material
Deep Learning Prerequisites: Linear Regression in Python
Deep Learning Prerequisites: Linear Regression in Python Data science: Learn linear regression from scratch and build your own working program in Python for data analysis. BESTSELLER 22,535 students enrolled Created by Lazy Programmer Inc. ย English [Auto-generated], Spanish [Auto-generated] Preview this course ย - GET COUPON CODE Free Coupon Discount Udemy Online Courses
YOLOv4 Object Detection Course
I started out wanting to learn AI Object Detection in Computer Vision... Now even though I have a masters degree in electronic engineering (M.Eng). It was still challenging for me to figure out. I had a lot of questions like... If Ubuntu, what version 16.04, 18.04, What kernel do I need? If I am training, what format does my dataset need to be in?
How cyber operations, social media and artificial intelligence areโฆ
When Russia invaded Ukraine in February 2022, the images of tanks and troops amassing and then crossing the border could make it seem like little has changed in the world of warfare. However, as the fighting in Ukraine progressed it also became clear how conflicts today are developing in new and very different ways. Many of the images we have seen were captured by satellites in space or on mobile phones, and the sharing of these on social media has helped to shape public attitudes and been used to circumvent or undermine state-sponsored messaging. We have also seen hackers declare cyberwar on Russia. In the latest episode of the WORLD:we got this podcast series Dr Tim Stevens and Dr Kenneth Payne, who are both based in the School of Security Studies in our Faculty of Social Science & Public Policy, explore how cyber operations, social media and artificial intelligence are changing the face of war.
Intro to Data Science Using Python: Your Best Starting Point
Welcome to "Introduction to Data Science Using Python" where you will set a good foot in the fields of Data Science and Machine Learning. I'm your instructor Ali Desoki and I start from scratch going clearly over all the points in the course along with hands-on practical exercises and projects to summarize all the skills you've learned. This course is designed for Beginners covering all Aspects of what you need to know to start in the fields of data science and machine learning with practice notebooks which summarize all the skills you've learned. At the end of this course, you will be able to analyze and manipulate data with python and be able to start your career in this field. The ideal student for this course is someone who looks to start in the mentioned fields from scratch.
Spatial Data Visualization and Machine Learning in Python
Learn how to visualize spatial data in maps and charts. Manipulate, clean and transform data. Welcome to the'Spatial Data Visualization and Machine Learning in Python' course. In this course we will be building a spatial data analytics dashboard using bokeh and python. We will be visualizing our data in a variety of bokeh charts, which we will explore in depth.
5 Career Tips from Women Leaders in Machine Learning - The New Stack
Understanding how important representation, role models, and mentoring had been to my own career journey, I started a network to support other Amazon employees looking to pursue a career in machine learning (ML) and artificial intelligence (AI). Open to anyone working at Amazon, the global Women in ML/AI group hosts regular networking events and organizes panel discussions with industry experts on career development. To discuss learnings from our professional journey, I sat down with fellow board members, including senior documentation manager Michelle Luna, senior software development manager Anna Khabibullina and general manager and product lead Shubha Pant. Here are some of the advice we found invaluable when launching and building a career in the field. Luna, Khabibullina, Pant and I are all proof that there are many paths into ML and AI -- from the traditional and linear, to the more unconventional.
Data science, machine learning, and analytics without coding
Solve real data science problems and add value quickly without needing to learn how to code. Do you want to super charge your career by learning the most in demand skills? Are you interested in data science but intimidated from learning by the need to learn a programming language? I can teach you how to solve real data science business problems that clients have paid hundreds of thousands of dollars to solve. I'm not going to turn you into a data scientist; no 2 hour, or even 40 hour online course is able to do that.
Natural Language Processing: NLP With Transformers in Python
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.
Water Leakage Localization for Smart Water Mgmt Using ML Techniques (March 2022)
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.