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4 Biggest Advantages of Pandas - DSBoost #15
Welcome to the 15th issue of DSBoost, the weekly newsletter where you can discover interesting people in the ML/AI world, get the main takeaways of a relevant podcast, and stay up to date with the latest news in the field!
💬 Interview of the week
This week we interviewed Avi, who is a Data scientist. Enjoy:
What did you study/are you studying (if your background is different from DS, how did you end up in the field)?
I am currently pursuing my bachelor’s degree in data science and analytics as a major. I am lucky that I made the right decision to get into data science with a degree as this field is just in the early stage of its lifecycle and still a lot of people depend on certification courses only. Degree programs are well structured and well designed to provide a strong foundation for long-term success.
What are your favorite resource sites and books (ML/AI)?
I have used Machine Learning Mastery extensively during the start of my data science learning journey.
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow by Aurélien Géron
Machine Learning using Python by Manaranjan Pradhan
Deep Learning with Python by Francois Chollet
Data Analytics using Python by Bharti Motwani
What got you into your current role (portfolio, certification, etc.)?
I have done a couple of end-to-end projects and some freelancing projects which I mainly got from my blogging work on Twitter and Medium.
What do you enjoy the most in your work?
I enjoy analytics thinking and framing problems in a way that solves users’ problems and makes an impact on the real world.
What tools do you use the most / favorite tools?
I use all the standard data science and ML tools such as Pandas, Matplotlib, scikit-learn, Keras, etc.
I am also learning cloud platforms like AWS and MLOps tools
Do you use ChatGPT or other Al tools during your work? If so, how do they help you? Do they change your approach to problems?
I use ChatGPT in my educational journey to simplify some concepts and find answers without juggling through tons of traditional text books. AI tools can help in quick knowledge checks and research some topics.
AI tools are becoming like assistants in the work I do. I am still learning how to use these tools effectively and build my own workflow accordingly.
What is your favorite topic within the field?
My favorite topic is statistics in the data science field.
Which one of the recent AI/ML models will have the most significant impact on the industry in your opinion?
I would say all the AI models which are coming up have their own application and they also need to be fine-tuned for effective usage in the industry. Talking about impact I think the GPT3.5 model has had the most impact since ChatGPT was built on top of it.
What are you currently learning or improving (topics you are interested in nowadays)?
I learn MLOps and also looking to learn more about LLMs and fine-tuning such models.
What is the biggest mistake you've made? (preferably DS related)
There are many mistakes I have made during my learning journey. I see them as a part of the road so not bothered about it all.
What is your most significant achievement? (preferably DS related)
There have been many achievements I saw in a short period of time like the Twitter audience I built, GitHub and Open source contributions to AI projects by Omdena, and writing a couple of data science blog articles across Analytics Vidhya and Medium.
🎙️ Podcast of the week
Super Data Science Podcast: Pandas for Data Analysis and Visualization — with Stefanie Molin
Advantages of Pandas:
Pandas has a market share advantage - you will see it everywhere, so this also means lots of examples, resources, and community.
It is well-tested.
Chaining can save you a lot of effort.
You can plot directly from Pandas! Matplotlib and Seaborn should be only used for advanced plotting.
Where Data Analysts should start?
It depends on the learning style, if you love statistics, start with that and add coding later, and vice versa. Staying positive and motivated is important and this approach can help.
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🧵 Featured threads
🤖 What happened this week?
Google's upcoming I/O event is expected to showcase major AI-focused updates, according to a CNBC report. One highlight will be the introduction of a new large language model (LLM) called PaLM 2, described as Google's most recent and advanced LLM. PaLM 2 has reportedly demonstrated its abilities in coding, math tests, creative writing, and analysis.
Midjourney has released version 5.1, which introduces significant improvements in image quality and style. The new version aims to provide more artistic and dramatic outputs while maintaining higher resolution and sharpness.