Deep Tech
Reporting, analysis and features from AIM's Deep Tech section.
Complete Guide To Descriptive Statistics in Python for Beginners
We are learning statistics because we can; observe the information properly, draw the conclusion from the large volume of the dataset, make reliable forecasts about business activity and improve the business process. To do all kinds of the…
Vijaysinh Lendave ·
Guide To Differentiable Digital Signal Processing (DDSP) Library with Python Code
DDSP is an audio generation library that uses classical interpretable DSP elements (like filters, oscillators etc.) with deep learning models.
Nikita Shiledarbaxi ·
Guide To Image Color Analyzer In Python
Yugesh Verma ·
Reinforcement Learning Comes To Android Phones
Ram Sagar ·
Complete Guide to Python Metaclasses
Python metaclasses is an abstruse OOP concept that lurks behind basically all Python code, it can be used to modify the behaviour of classes.
Aditya Singh ·
Ways To Implement Instance Segmentation By Location with SOLO and SOLOv2
Nikita Shiledarbaxi ·
Guide to Torchmeta- A Meta-Learning library for PyTorch
Aishwarya Verma ·
Why Eleven 9s Is Called The Gold Standard Of Durability In Cloud
Ram Sagar ·
Attend The Full Day Hands-On Workshop On Reinforcement Learning
Sejuti Das ·
Why R Users Should Tap Python To Up Their Programming Game
Shraddha Goled ·
Generate Your ML Code In Few Clicks Using Train Generator
TrainGenerator is a Streamlit based web app for machine learning template code generation surpassing the different stages of data loading, preprocessing, model development, hyperparameter setting, and declaring other such constraints for c…
Jayita Bhattacharyya ·
How To Leverage GPUs For Recommendation Engines At Scale
Ram Sagar ·
Guide To Asymmetric Non-local Neural Networks Using PaddleSeg
PaddleSeg is an Image segmentation framework based on Baidu’s PaddlePaddle(Parallel Distributed Deep Learning). It provides high performance and efficiency, SOTA segmentation models optimized for MultiNode and MultiGPU production systems.
Pavan Kandru ·
Python Guide to HiSD: Image-to-Image translation via Hierarchical Style Disentanglement
HiSD controls the image-to-image translation process via Hierarchical Style Disentanglement based on tags, attributes and styles.
Rajkumar Lakshmanamoorthy ·
Guide To ResNeSt: A Better ResNet With The Same Costs
ResNeSt architecture combines the channel-wise attention with multi-path representation into a single unified Split-Attention block.
Aditya Singh ·
Complete Guide to ENCONTER: Entity Constrained Insertion Transformer for Language Modeling
Entity Constrained Insertion Transformer, shortly known as the ENCONTER, introduces entity constraints to control text generation efficiently
Rajkumar Lakshmanamoorthy ·
New Hackathon For Data Scientists — Workation Price Prediction Challenge
Sejuti Das ·
Guide To Interactive Image Synthesis With Anycost GANs
Anycost GAN supports fast, responsive previews during image editing by executing the generator at a wide range of computational costs.
Aditya Singh ·
Machine Learning Deployment Is The Biggest Tech Trend In 2021
Ram Sagar ·
Guide To THiNC: A Refreshing Functional Take On Deep Learning
THiNC is a lightweight DL framework that makes model composition facile. It’s various enticing advantages like Shape inference, concise model representation, effortless debugging and awesome config system, makes this a recommendable choice…
Pavan Kandru ·