100% FREE book to prepare for your Deep Learning interview. With real-world interview problems and solutions. Here is the link: https://
arxiv.org/pdf/2201.00650
.pdf
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@abacusai
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Free Deep Learning Interview Preparation Book with Real-World Problems
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Follow Abacus AI for More Upcoming Content
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If you enjoy this content, follow @abacusai
! There's much more coming! -
Building ML Systems: Key Components and Solutions
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Building machine learning systems is hard. Some of the components you need: 1. Data sources
2. Data pipelines
3. Feature stores
4. Model training
5. Model evaluation
6. Model deployment
7. Model monitoring
8. Predictions API At @abacusai we help you with this! -
Follow Abacus AI for more upcoming content
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If you enjoy this content, follow @abacusai
! There's much more coming! -
Free Prompt Engineering Guide for AI Models
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The Prompt Engineering Guide contains papers, learning materials, and tools to help with prompt engineering. If you want to get better at using ChatGPT, Stable Diffusion, Dalle-2, and any other modern large model, take a look at this. 100% FREE. Link: https://github.com/dair-ai/Prompt-Engineering-Guide
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Abacus AI’s Core Research Areas in AI and Machine Learning
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At @abacusai we are doing active foundational research in the following areas – Neural architecture search
– Code gen LLMs
– Pre-trained forecasting
– NNs for tabular data
– LLMs for Enterprise AI -
Machine Learning Practice Projects to Build Your Skills
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Sample projects you could build to practice machine learning: 1. Detect movement in a video
2. Stock trading bot
3. Track a person in a video
4. Speech emotion recognition
5. License plate recognition
6. Identify the language used in a text 1 of 2 -
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If you enjoy this content, follow @abacusai
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Free Book on Multimodal Deep Learning Available for Download
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100% FREE book about Multimodal Deep Learning. Multimodal learning is about learning from data of multiple modalities, for example, text, images, video, etc. Download it here: https://
arxiv.org/pdf/2301.04856
.pdf
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End-to-End ML Platform: Complete Feature Set Overview
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This is what an end-to-end ML platform looks like: • Streaming Pipelines
• Data Wrangling
• Real-Time Feature Store
• SOTA Models
• Notebook Hosting
• Training Pipelines
• Plug & Play Models
• Batch Predictions
• Model Monitoring & Drift Take a look at @abacusai
.