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The Top ML Papers of the Week (April 29 - May 5): - Med-Gemini - When to Retrieve? - Kolmogorov-Arnold Networks - Multimodal LLM Hallucinations - Self-Play Preference Optimization - In-Context Learning with Long-Context Models ...
Scaling deep retrieval with TensorFlow Recommenders and Vertex AI Matching Engine- really cool article 🤖 @googlecloud cloud.google.com/blog/products/…
There are hundreds of machine learning algorithms out there. But you only need a few. Here are 9 of the most useful choices: 1. Transformers 2. LSTMs 3. CNNs 4. GBT 5. K-Means 6. Naive Bayes 7. Logistic Regression 8. Reinforcement Learning 9. KNN
How can a teacher understand youth with such a system? It bored me. The teachers behaved like sergeants. I wanted to learn what I wanted to know, but they wanted me to learn for the exam. What I hated most was the competitive system there, and especially sports. Because of this,…
Albert Einstein on his school and Education system💡 It bored me. The teachers behaved like sergeants. I wanted to learn what I wanted to know, but they wanted me to learn for the exam. What I hated most was the competitive system there, and especially sports. Because of this, I…
"If a 'religion' is defined to be a system of ideas that contains unprovable statements, then Gödel taught us that mathematics is not only a religion, it is the only religion that can prove itself to be one." -- John D. Barrow, The Artful Universe (1995)
💥 An overview of machine learning algorithms! Source: Ravit Jain #MachineLearning #Algorithms #DataScience
Why does a scientist study nature? by Henri Poincaré 💭 The scientist does not study nature because it is useful to do so. He studies it because he takes pleasure in it, and he takes pleasure in it because it is beautiful. If nature were not beautiful it would not be worth…
Brilliant, I love it! Everyone should checkout #Mojo 🔥 - a revolutionary new programming language that supercharges #Python, and AI. Read more via modular.com/mojo today! @modular_ai
📣Ready to dive deep into the world of #MachineLearning with Graphs? 🌐 Our new online class explores how diseases & information spread, traffic & weather predictions, & so much more! Join us, & make sense of the world's complex data🚀. online.stanford.edu/courses/xcs224… We kick off on…
Awesome overview of #ChatGPT from Yogesh Haribhau Kulkarni!🤯 🔗 linkedin.com/feed/update/ur…
Knowledge Graphs + Large Language Models = The ability for users to ask their own questions? A great article by @petertimebandit , thank you for that! link.medium.com/M8JrJayhhzb
💥 Skills needed to become a data scientist. What else would you add to the list? Source: @kennedykwangari #Skillset #DataScience #AI
Colombian rivers! Coloured according to their drainage basin, and scaled by discharge. #SouthAmerica #Colombia #Rivers #DrainageBasin #Python #Geography #DataViz
Time for you to take a short break. Here is a weekly joke, hoping it to bring laughs for you all! #WeeklyJoke #Weekend #DataScience #DSDojo
A day in the life of people Each dot represents a person, each color an activity. It reminds us of the importance of understanding people's lives . Where are you in your day when reading this post? :)
Follow us for science-infographics like: "The History of Math"
Let's summarize things: 1. Problem type 2. Model performance 3. Explainability 4. Model complexity 5. Data availability 6. Dimensionality 7. Training time and cost 8. Inference time Are there other factors you consider when choosing what algorithm and technique to use?
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