The Web3 Development Roadmap - 2022 Basics of CS → HTML, CSS & JavaScript → Basics of Blockchain → Git & GitHub → Solidity → React → Ether.js → The Graph → Build Project → Apply 👑

Did you know you can merge #Python dictionaries using the `update()` method? You can also use `update()` to update multiple key/value pairs in a dictionary too! Here's an example:

✅ Advanced Pandas Techniques for Data Scientists medium.datadriveninvestor.com/5-cool-advance… #Python #DataScience #MachineLearning #DataScientist #Programming #Coding #100DaysofCode #hubofml #visualization #NLP

#Python Pro Tip 🐍‼️ You can use `zip()` and `dict()` to turn two lists of equal length into a dictionary! Here's how:

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Senior developers teaching junior developers to code x.com/videosvecagand…

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💥 List of Python libraries & frameworks! #Python #Framework #DataScience

All you Need to Know About AutoEncoders in 2022. #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode geni.us/AutoEncoders-2…

Cool project

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New release of Hugging Face transformers includes a new pipeline called Document Question Answering ❓📄 This is a pipeline you can use to extract information from PDFs! Let's take a closer look 👀

We trained a transformer called VIMA that ingests *multimodal* prompt and outputs controls for a robot arm. A single agent is able to solve visual goal, one-shot imitation from video, novel concept grounding, visual constraint, etc. Strong scaling with model capacity and data!🧵

Same here in my home country

"The effectiveness of BERT arises from: 1. Pre-training over large amounts of raw textual data via self-supervised learning 2. Crafting rich, bidirectional feature representations of each token within a sequence" Learn more from Cameron R. Wolfe, Ph.D.'s post. buff.ly/3DdsfW1

Mckinsey makes millions on a single presentation.....yeah👀 Here is the central business storytelling framework I learned in my 4 yrs there🧵👇

3 research papers you should read to understand Transformers 🦾 better. 1. "Attention is All You Need" Google AI that started the transformer revolution 2. Switch Transformers Google AI 3. TAPAS Google AI A Thread 🧵👇

2) “Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity” by Google AI Introduced the biggest transformer model ever built with over one trillion parameters. arxiv.org/pdf/2101.03961…

3) “TAPAS: Weakly Supervised Table Parsing via Pre-training” by Google AI Introduced a model that extends BERT’s architecture to work with tabular datasets. arxiv.org/pdf/2004.02349…