Amazon India is inviting applications from students for the second edition of its online Machine Learning (ML) summer school. The course aims to teach key machine learning technologies by scientists at Amazon and to make the candidates industry-ready for careers in science. The free course, which was launched in 2021, is open to students enrolled in any recognised institute in India, who are expected to graduate in 2023 or 2024. Rajeev Rastogi, vice president of applied science in ML, says, "The tutorial sessions covering the right mix of theoretical and practical knowledge will be delivered by our ML scientists who are experts in their field. This programme will be a platform to help foster ML excellence and strive towards developing applied science skills in young talent."

The DeepLearning.AI TensorFlow: Advanced Techniques Specialization introduces the features of TensorFlow that provide learners with more control over their model architecture and tools that help them create and train advanced ML models. This Specialization is for early and mid-career software and machine learning engineers with a foundational understanding of TensorFlow who are looking to expand their knowledge and skill set by learning advanced TensorFlow features to build powerful models.

The practice of investment management has been transformed in recent years by computational methods. This course provides an introduction to the underlying science, with the aim of giving you a thorough understanding of that scientific basis. However, instead of merely explaining the science, we help you build on that foundation in a practical manner, with an emphasis on the hands-on implementation of those ideas in the Python programming language. This course is the first in a four course specialization in Data Science and Machine Learning in Asset Management but can be taken independently. In this course, we cover the basics of Investment Science, and we'll build practical implementations of each of the concepts along the way.

This is the fifth course in the IBM AI Enterprise Workflow Certification specialization. You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones. This course introduces you to an area that few data scientists are able to experience: Deploying models for use in large enterprises. Apache Spark is a very commonly used framework for running machine learning models. Best practices for using Spark will be covered in this course.

Expand your NLP portfolio using BERT and Haystack to answer all your questions! If you're trying to learn Natural Language Processing (NLP), make a Discord Bot, or are just interested to play around with Transformers for a bit, this is the project for you! In this example, we will create a Chatbot that knows everything about Dragon Ball, but you can do about anything you want! It can be a chatbot that answers questions about another series, a university course, the laws of a country, etc. Firstly, let's see how that is possible with BERT. BERT is a Machine Learning technique for NLP created and published by Google in 2018.

There is a worrying shortfall in skills required for a career in AI. Although technical capabilities are vital for a career in the sector, problem solving is considered the most critical soft skill needed for tech roles among all survey participants (up to 37%). However, around a quarter of tech recruiters (23%) have difficulty finding applicants with this aptitude along with shortfalls in critical and strategic thinking, according to IMB's report'Addressing the AI Skills Gap in Europe'. Also, nearly seven in 10 tech job seekers and tech employees believe that potential recruits lack the skills necessary for a career in AI. As AI moves into the mainstream, specialist tech staff are working more closely than ever with business managers.

Are you looking for the Udacity AI Product Manager Nanodegree Review?… If yes, this latest Udacity AI Product Manager Nanodegree Review will help you to decide whether to enroll in the program or not. So, without further ado, let's get started- You are looking for Udacity AI Product Manager Nanodegree Review, which means you have a doubt about whether to enroll in this program or not. And this doubt is common because Udacity Nanodegree Programs are expensive as compared to other MOOCs programs. So, I will help you to decide whether to invest in this expensive Nanodegree Program or not. Along with that, I will also share my tips and tricks to save a few bucks while enrolling in the Udacity AI Product Manager Nanodegree Program.

This is the second (and last) article of the "Understanding AutoEncoders with an example" series. In the first article, we generated a synthetic dataset and built a vanilla autoencoder to reconstruct images of circles. We'll be using the same dataset once again, so please check the section "An MNIST-like Dataset of Circles" for a refresher, if needed. We'll also understand what the famous reparametrization trick is, and the role of the Kullback-Leibler divergence/loss. You're invited to read this series of articles while running its accompanying notebook, available on my GitHub's "Accompanying Notebooks" repository, using Google Colab: Moreover, I built a Table of Contents to help you navigate the topics across the two articles, should you use it as a mini-course and work your way through the content one topic at a time.

The following sentence is annoying, but also true: the best time to learn Git was yesterday. Fortunately, the second best time is today! Git is an essential tool for work in any code-related field, from data science to game development to machine learning. This course covers everything you need to know to start using Git and Github in the real-world today! The course's 20 sections are broken down into four separate units: We start off with Git Essentials. The goal of this unit is to give you all the essential Git tools you need for daily use.

Databricks is founded by the creators of Apache Spark, Databricks combines the best of data warehouses and data lakes into a lakehouse architecture. Databricks is an American enterprise software company founded by the creators of Apache Spark. The company has also created Delta Lake, MLflow and Koalas, open source projects that span data engineering, data science and machine learning. Databricks develops a web-based platform for working with Spark, that provides automated cluster management and IPython-style notebooks. Gartner has classified Databricks as a leader in the last quadrant for Data Science and Machine Learning platforms.