Build Machine Learning Python Apps with TensorFlow and WayScript
We explore 18 machine learning practices that that you can apply when building your machine learning application. Machine Learning and Deep Learning (AI, in general) are no longer just buzzwords. Because of all these things building machine learning-based applications is not an easy task. There are several areas where data scientists, software developers and DevOps engineers need to work together in order to make a high-quality product.
This is a PyTorch implementation of ShiftAddNet: A Hardware-Inspired Deep Network published on the NeurIPS 2020.
Nowadays, Python is one of the most popular programming languages in AI and Machine Learning. Python is known for its useful libraries and packages that make programming possible even for people without a software engineering background
CARLO stands for CARLA - Low Budget. CARLO is definitely less realistic than CARLA, but it is much easier to play with. Most importantly, you can easily step the simulator in CARLO, and it is computationally much lighter
Deep Learning Chatbot R&D
Gradient descent is an optimization technique that can find the minimum of an objective function. It is a greedy technique that finds the optimal solution by taking a step in the direction of the maximum rate of decrease of the function.
PyTorch is one of the fastest-growing Python-based frameworks for deep learning. Let’s have a look at the basics and how to build and deploy a model using Machine Learning. A practical walkthrough on getting started with PyTorch. Let’s look at the benefits of using ML project and a quick comparison between PyTorch and NumPy. Getting Started with PyTorch – Deep Learning in Python
In this video, I will be showing you how to build a machine learning model for computational drug discovery from scratch. Firstly, we will be calculating molecular descriptors (using PaDEL-Descriptor software),
This SEO-focused SaaS uses machine learning to detect website content and architecture issues. Here's why you might want to consider partnering with them. Machine Learning SEO Software Seeks International Partners
In this video, we will cover the introduction of Clustering in Machine Learning, then we will understand the concept of clustering with the help of an example. Finally, we understand the areas and applications of clustering in this video. The code for the video (if any) can be found on GitHub
Image annotation plays a significant role in machine learning, enabling AI –models to detect and recognize objects.
High-performance multiple object tracking based on YOLOv3/v4, Deep SORT, and optical flow. Deep learning models are usually the bottleneck in Deep SORT, which makes Deep SORT unscalable for real-time applications. This repo significantly speeds up the entire system to run in real-time even on Jetson.
This is the video tutorial#09 for Ai Machine Learning Course for Android Developers using TensorFlow Lite. This course is designed and created for Android developers who want to learn Machine Learning & deploy machine learning models in their android applications using TensorFlow Lite. If you have very basic knowledge of Android App development and want to learn Machine Learning use in Android Applications this course is for you. This is an incredible ML course for Android Developers 2021. This will get you started in creating your first deep learning model || machine learning model and Android Application using both JAVA & Kotlin, Tensorflow Lite, and Android studio. We will learn about machine learning and deep learning and then we will train our first model and deploy it in android application using Android studio. In this video tutorial#09 you will learn about python loops and iterations & for loop in python & while loop in python for machine learning (data science) course. Loops in Python for Machine Learning & AI || Python For Loop & Python While Loop | Tensorflow Lite
This primer will help you cover much of the groundwork and allow you to craft your own AI strategy: tasks, data, third-party platforms, and hiring.
Machine learning is one of the most popular topics. It is also hard. This beginner-friendly roadmap will help you start with machine learning the easy way.
On a high level, Machine Learning is the union of statistics and computation. The crux of machine learning revolves around the concept of algorithms or models which are in fact statistical estimations on steroids. The Ultimate Guide to Evaluation and Selection of Models in Machine Learning - neptune.ai
If you’re an AI professional or aspire to be one, one thing you must be aware of is: machine learning algorithms are your closest aid and ally. These
After working on the model building, the next step in the machine learning life cycle is usually the deployment in the real-world scenario to perform actionable tasks. In most cases, the model is deployed via the web interfaces, android apps, or IoT. Where the website deployment requires a lot of extra effort to set up the front-end, android apps seems a reasonable solution, and that too when the app is built in Python! In this article, I will walk you through building apps using Python, which will be a cross-platform application, meaning it can be converted into android apps and IOS too. How to Deploy Machine Learning Models in Android Apps using Python
This article compiles the 38 top Python libraries for data science, data visualization & machine learning,