Do you guys/girls also bookmark lots of resources to read after? Well I am actually one for those who reads them 😂 I wanted to share some of those resources from this year, you might also find them useful:
- 10 Must-Read Machine Learning Books
- Medicine's Machine Learning Problem
- AlphaSignal
- Neural Netoworks and Deep Learning
- Data Mining and Machine Learning: Fundamental Concepts and Algorithms
- Deep Learning Book
- How I Prepared for the TensorFlow Developer Certification
- Classifying emotions using audio recordings in Python
- How to download and visualize your Twitter network
- 17 types of similarity and dissimilarity measures used in data science
- New Courses: Machine Learning Engineering for Production
- What is Data Extraction? A Python Guide to Real-World Datasets
- How to build an AutoML app in Python
- How to Download High-Resolution Satellite Data for Anywhere on Earth
- Why You Shoudn't Hire More Data Scientist
- How To Deploy Machine Learning Models
- The Last Mile in Shipping Data Science Projects Well
- Exploratory Data Analysis, Visualization, and Prediction Model in Python
- Data Science, Meaning, and Diversity
- 5 Data Science Open-source Projects You Should Consider Contributing to
- Lifecycle of an ML Project
- Network Analysis
- Neural network from TENET exploiting time inversion
- Social Network Analysis: From Graph Theory to Applications with Python
- Deploying An ML Model With FastAPI - A Succint Guide
- MLOps Best Practices for Data Scientists
- How do I know which graph to use?
- Semi-Automated Exploratory Data Analysis (EDA) in Python
- How to deploy Machine Learning models as a Microservice using FastAPI
- How to use Plotly.js in React to Visualize and Interact with Your Data
- Understanding Bias and Fairness in AI Systems
- What do you make of this?
- Data Science. The Central Limit Theorem and sampling
- Automating Machine Learning tasks using EvalML Libariry
- To Learn Data Science Faster, Teach It
- Announcing Power BI in Jupyter
- Awesome community detection
- Does MLOps Live Upto The Hype?
- MLOps Basics
- Google colab notebooks are already running Deepmind's AlphaFOld v.2
- Not another Qlik Sense Spotify App
- Creating a Modern, Open Source MLOps Stack at Home
Can you guess what I've been working on based on this?🤔
Thank you for these resources, you may be interested to save them in the decentralized collective research tool https://www.publicdomain.live/
Nice, thanks for this. Always sharing the best resources from your side!