If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
The learning rate is often considered to be the most important hyper-parameter when training a model. Choosing the optimal learning rate can greatly improve the training of a neural network and can prevent any odd behavior that may occur during stochastic gradient descent. Stochastic gradient descent (SGD) is an optimization algorithm that helps the loss function converge to the global minimum, or where the loss is at its lowest point. It behaves just like gradient descent, but also has batches to increase the computational efficiency. Gradient descent is performed to each of these smaller batches instead of the entire training set size.
We have a long newsletter this week as many new NLP repos were published as tech nerds return from their Summer vacation. This week I'll add close to 150 new NLP repos to the NLP Index. So stay tuned for this update, it will drop this week. Embeddinghub is a database built for machine learning embeddings. It is built with four goals in mind.
Building a machine learning model requires a series of steps, from data preparation, data cleaning, feature engineering, model building to model deployment. Therefore, it can take a lot of time for a data scientist to create a solution that solves a business problem. To help speed up the process, you can use Pycaret, an open-source library. Pycaret can help you perform all the end-to-end processes of ML faster with few lines of code. Pycaret is an open-source, low code library in python that aims to automate the development of machine learning models.
Data science and data scientist's job market is constantly evolving. Every year, there are so many new things to learn. While some tools rise and others fall into oblivion, it becomes highly essential for a data scientist to keep up with the trends and have the necessary knowledge and skills to use all the tools that make their job easier. Here are the top 15 tools that every data scientist should bring to work to become more effective at their job. For a data scientist, their mind is one of the best tools that keep them one step ahead of the competition.
This library is the official extension repository for the python deep learning library Keras. It contains additional layers, activations, loss functions, optimizers, etc. which are not yet available within Keras itself. All of these additional modules can be used in conjunction with core Keras models and modules. As the community contributions in Keras-Contrib are tested, used, validated, and their utility proven, they may be integrated into the Keras core repository. In the interest of keeping Keras succinct, clean, and powerfully simple, only the most useful contributions make it into Keras.
TensorFlow is Google's open-source software library for machine learning that developers and researchers can use for a range of application areas. The well-known and widely spread library comes in different flavors ready to run on various operating systems and hardware. Specifically, the TensorFlow Lite for Microcontrollers (TFLM) version is designed to run on microcontroller systems where the hardware resources are more limited compared to larger computerized systems. The footprint of TFLM is typically in the order of only 10's of kB. Now you can develop solutions with TensorFlow for the Spresense microcontroller board from Sony.
Deep Learning A-Z™: Hands-On Artificial Neural Networks Free Coupon Discount - Learn to create Deep Learning Algorithms in Python from two Machine Learning & Data Science experts. Templates included. BESTSELLER 4.6 (25,470 ratings) Created by Kirill Eremenko, Hadelin de Ponteves, SuperDataScience Team English, French [Auto-generated], 4 more Preview this Udemy Course - GET COUPON CODE 100% Off Udemy Coupon . Free Udemy Courses . Online Classes
MLOps is the machine learning operations counterpart to DevOps and DataOps. But, across the industry, definitions for MLOps can vary. Some see MLOps as focusing on ML experiment management. Others see the crux of MLOps as setting up CI/CD (continuous integration/continuous delivery) pipelines for models and data the same way DevOps does for code. Other vendors and customers believe MLOps should be focused on so-called feature engineering -- the specialized transformation process for the data used to train ML models.
A Complete Guide on TensorFlow 2.0 using Keras API, Build Amazing Applications of Deep Learning and Artificial Intelligence in TensorFlow 2.0 Created by Hadelin de Ponteves, Kirill Eremenko, SuperDataScience Team, Luka AnicinPreview this Course - GET COUPON CODE Welcome to Tensorflow 2.0! TensorFlow 2.0 has just been released, and it introduced many features that simplify the model development and maintenance processes. From the educational side, it boosts people's understanding by simplifying many complex concepts. From the industry point of view, models are much easier to understand, maintain, and develop. Deep Learning is one of the fastest growing areas of Artificial Intelligence.
Everyone knows how Covid-19 pandemic devastated the nightlife industry with social distancing, lockdowns, mask-wearing and early curfews. These nightlife spaces were shuttered because they had been deemed non-essential services and places of easy transmission for the coronavirus. Now that central and state governments in India have eased the restrictions people can finally enjoy a breather, commemorating a special occasion or just spending time with friends over food and drinks. In a city like Pune, which boasts a happening nightlife scene, there's always a party happening somewhere or the other. Widely known as the "IT hub of India", "Automobile and Manufacturing hub of India" and "Oxford of the East", Pune is known for its lifestyle, pleasant weather and just… everything good.