I share my learning journey into Data Science with my amazing LinkedIn friends, follow me and let's grow together!

For downloadable ML/ AI/ Data Science learning materials, please check my previous posts.

** Opinions are my own and not the views of my employer **

Alex Wang

Data Scientist

AI4Diversity

AI 4 Diversity (AI4D) is a nonprofit global initiative that engages and educates diverse communities about AI to benefit global society.

Member of Operation Team

Quantium

Global Market

Deloitte Australia

Business Algorithms

University of Technology Sydney

Casual Academic

Hackmakers

Pactera

Data Analyst

I share my learning journey into AI and Data Science here, click 'follow' and let's grow together!

For open access resources, productive tools, and learning materials in Machine Learning/ Data Science and AI Applications, please check my previous posts.

** Opinions are my own and not the views of my employer **

Member of Global Committee

It is voluntary role helping the global management team. 
AI 4 Diversity (AI4D) is a nonprofit global initiative that engages and educates diverse communities about AI to benefit global society.

Heyyyy! If the coding book were this cute, I would have started learning when I was 6! 😃

Data Analytics - Life is Short, I Use Python! 
https://lnkd.in/gcwidPPg

The best Python libraries for generative AI!
https://lnkd.in/g8tHehEr

Python code for AI
https://lnkd.in/g2VUjmrV

Take a screenshot of a 𝐌𝐚𝐭𝐡 𝐟𝐨𝐫𝐦𝐮𝐥𝐚 -> 𝐭𝐡𝐞 𝐜𝐨𝐫𝐫𝐞𝐬𝐩𝐨𝐧𝐝𝐢𝐧𝐠 𝐋𝐚𝐓𝐞𝐗 𝐜𝐨𝐝𝐞 in Python
https://lnkd.in/gVG9kJsC

Self-study resources for Machine Learning and Data Science
https://lnkd.in/gCyVFW9K
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I share my learning journey with all my LinkedIn friends, click follow and let's grow together!

For more learning materials on AI, Machine Learning, and Data Science, please check my previous posts. Alex Wang

#datascience #python #programming #machinelearning

"Still hiring humans?" That's what this billboard from Bland AI, a conversational AI lab, says. It was spotted earlier this morning in downtown San Francisco.

Underneath it, there's a phone number and when you call it, an AI answers. On top of AIs doing customer support and receptionist work, It's pretty interesting to think of things that AI is capable of doing that we aren't...

For example, we all know the stat that a lead is 400% more likely to convert to a customer if they're called back within 1 minute - but only 1% of businesses do it. 

You could easily imagine an AI making a phone call to a lead. It would work 24/7, be cheaper than a human, and integrate straight into a CRM.

That's effectively one of the many things that Bland already does. But I think this does raise serious questions about automation. Where do you think all of this is going? 

Try talking to the AI on the phone 
http://bland.ai/

or explore something even more surprising.
https://lnkd.in/gNj5ghZa

#artificialintelligence #innovation #producibility #aitools

I share my learning journey into AI and Data Science with my amazing LinkedIn friends, please make sure you’ve clicked the 'follow' button and let's grow together!

For resources, productive tools, and learning materials in Machine Learning/ Data Science and AI Applications, please check my previous posts.

** Opinions are my own and not the views of my employer **

Prasad Bharadwaj

Learn AI Together - I share my learning journey into AI and Data Science here, 90% buzzword-free. Follow me and let's grow together!

LLMs landscape with their associated bots (such as ChatGPT)

We might think that choosing the largest model is the way to go for most use cases due to its power, but larger models often come with higher computing costs, complexity, and variability. 

A better approach is to pick the right-sized model for the specific use case we have. It’s all about finding the sweet spot between performance, speed, and cost.

If we consider other additional benefits the model might deliver, like lower latency and greater transparency into the model inputs and outputs, we may find a smaller, less expensive model to be more preferable, even if it may not offer performance or accuracy metrics on par with a more expensive one.

Also, deploying on-premise gives greater control and more security benefits compared to a public cloud environment, but it’s an expensive proposition, especially when factoring in model size, compute power, and the number of GPUs it takes to run a single LLM.

✔️I share my learning journey here. Join me and let's grow together.

For more on AI and learning materials, please check my previous posts. Alex Wang

#generativeai #artificialintelligence #technology #chatgpt

Thomas Winkler

In the era of AI, is it still necessary to learn programming to become a software engineer or data scientist?

It is true that programmers will likely spend less time writing code in the future and will instead focus more on monitoring and managing AI outputs, ensuring their quality and continuous improvement.

This shift does not mean replacing existing skill sets. Instead, it involves adding new soft skills necessary for a more managerial role. A deep understanding of the underlying code and algorithms will still be very needed.

As AI improves in coding, we can focus less on memorizing syntax and more on developing inherent skills and techniques. Free online courses from top uni, happy learning!

𝐌𝐈𝐓
Intro to Computer Science & Programming with Python
https://lnkd.in/gvKcue_x

Machine Learning with Python: From Linear Models to Deep Learning
https://lnkd.in/gxipFcrv

𝐒𝐭𝐚𝐧𝐟𝐨𝐫𝐝
Statistical Learning with Python
https://lnkd.in/gqUTrsmg

Statistical Learning with R
https://lnkd.in/gEQnZC-a

A fun trick:

Take a screenshot of a 𝐌𝐚𝐭𝐡 𝐟𝐨𝐫𝐦𝐮𝐥𝐚 -> 𝐭𝐡𝐞 𝐜𝐨𝐫𝐫𝐞𝐬𝐩𝐨𝐧𝐝𝐢𝐧𝐠 𝐋𝐚𝐓𝐞𝐗 𝐜𝐨𝐝𝐞 in Python
______________________
pip install "pix2tex[gui]"
______________________

✔️I share my learning journey here, join me and let's grow together.

For more on AI, ML, Data Science, please check my previous posts. Alex Wang

#programming #datascience #machinelearning #python

A nice summary of the data analysis process!

It is a complex process that involves more than just crunching numbers. In very few cases can a data analyst's job start directly from receiving a dataset from the client.

More often than not, you may need to spend hours and hours in meetings with clients or other stakeholders to get the right access or the right data, especially when the project involves collaboration across multiple departments. And sometimes, you may need to go back to the first step to adjust the plan when certain data is not available.

This is actually a big part of the data analysis work.

You may also find yourself consistently working in an ambiguous space that is evolving fast and requiring a broad skillset. Meanwhile, the wide range of skills needed has led to a growth in data science specializations. 

It may sound overwhelming, but like many other jobs, you don't have to know it all to start. Learn the fundamentals, plus Excel, SQL, and Python basics, and you're good to go! 🚀

Continue learning during your job, you will find the way you want to go. 👩🏻‍💻

Img:tutort
_________________

✔️I share my learning journey here, join me and let's grow together.

For free learning materials on Data Science & ML, please check my previous posts. Alex Wang

#datascience #dataanalysis #machinelearning

'Setting up generative AI pilots is easy; scaling them to capture material value is hard.'

While GenAI has the potential to revolutionize banking, scaling it up to maximize benefits is a challenge. 

Unlike traditional change management, GenAI requires not just leadership support but also navigating new technical complexities, increased collaboration between business and data teams, and adapting to a fast-changing environment.

Banks with strong existing AI talent will have an advantage in overcoming these challenges.

✔️Live webinar that you will lean more about it https://bit.ly/3PY2HlB

Reference/ Read full report https://lnkd.in/gDGj3y5f

For more on AI and learning materials, please check my previous posts. Alex Wang

#artificialintelligence #bigdata #technology #banking

AI understand human emotions…?

Bland AI is making AI phone agents that can understand emotions, respond in any voice, and be programmed to do anything. 

This has drastic implications for the job market.

How? Let's see one example:

🤖Speed to lead: In sales, if you call a lead back within 1 minute, they’re 400% more likely to convert. But only 1% of businesses do it. Now AI can do millions of these calls simultaneously in an instant. All while being hooked up to a CRM and calendar. 

Customer support, sales, call centers, etc. It’s being used for everything.

✔️You can try the emotion feature by signing up as an enterprise or try calling the AI Phone Agent on their website https://www.bland.ai/

Will we talk to AI more than humans in the future? What's your thought on this?

#artificialintelligence #machinelearning #technology

Nicolas de Maussion

Which countries are most interested in GenAI? 

The ranking is quite surprising, and fun to read!

Key Findings (from ElectronicsHub report)

- The Philippines has the highest monthly search volume for AI tools overall: mostly for text AI.

- ChatGPT is the most-searched GenAI tool in most countries (65), including the U.S. (not surprised by this)

- Quillbot is the most-searched tool in the second-most countries (61) but has the highest search volume overall (12 m global searches per month).

Which country surprises you the most? 👩🏻‍💻

 Also, free AI workshops to get hands-on experience

✔️Kafka Unleashed: Powering Real-Time AI with Streaming Data https://bit.ly/3JiAPF9

✔️Accelerate MongoDB® Apps to Drive 100x Faster Analytics and AI https://bit.ly/49AOYrN

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For more on AI and learning materials, please check my previous posts. Alex Wang

#artificialintelligence #chatgpt #technology #innovation

Top AI courses for professionals

Besides the courses I tried and can recommend, I've also curated a list of 5 newly released courses that have great structure and a practical focus. (marked in the image)

Most course lengths are between 3-6 months for part-time study. They are designed for beginners to become job-ready. You can definitely finish earlier if you have some foundation or can spend more than 2 hours per day.

As a bonus, here's an awesome AI workshop coming up, free as well
0) https://bit.ly/3JsflWc

Courses link
1) https://bit.ly/3xGUMCJ

2) https://bit.ly/4d5MtR5

3) https://bit.ly/3QbvbZ9

4) https://bit.ly/3U9KsuR

5) https://bit.ly/3JMdL1P

6) https://bit.ly/3Q8Qjz2

7) https://bit.ly/3w4b8oD

8) https://bit.ly/3UsEJBH

9) https://bit.ly/446cQT6

I used Coursera, but you can find all those courses on other platforms as well by searching for the course name. Some courses may require payment to receive the final certificate, but all of them are free to learn.

ps, If you're new to Coursera, there's a 7-day free trial you can take advantage of!

✔️I share my learning journey here. Join me and let's grow together.

For more on AI and learning materials, please check my previous posts. Alex Wang

#artificialintelligence #technology #machinelearning #datascience #bussiness

Tricks to stay motivated - for both learning and working!

1- If you feel lost motivation or direction, do nothing and feel guilt-free.

Interestingly, the dopamine level will slowly clam up again when you do nothing at all; allow yourself to rest long enough, and more motivation will be gathered.

2- Do something that you 'really hate' (but good for you eventually!). This will help you feel the increase in dopamine even quicker!

I usually go with workouts, things like squats help me a lot in getting myself back into motivated mode. Most of the interesting ideas I had were happening during exercise.

What is happening here is that you would have a big decrease in dopamine when you do things you dislike and are difficult, but after a dip in dopamine, an increase comes after you finally finish it. With that spike in dopamine; it correlates to having a burst of motivation.

The image I attached is from research by Uni of Illinois, another effective way that helps me a lot when I am stuck with a problem or can't come up with new ideas - start walking! Outdoor is even better. 🚶🏻‍♀️

Researchers provided evidence that walking supports cognitive performance and may be necessary for effective functioning across the lifespan.

Last tip, don't be too harsh on yourself! Upskilling/ learning is a lifelong journey, take your own pace. 
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I share my learning journey here. Join me and let's grow together.

For more on AI and open-access online courses, please check my previous posts. Alex Wang

I came across a couple of reports/ studies this morning. It's interesting to see that each firm has a different ranking of which country is going to lead the way in this AI revolution we are currently in. 

PWC ranks countries based on the number of AI startups from 2013 to 2022. The US is the absolute number one, and the private investment during these 10 years is more than the sum of the rest of the top 10 countries. China and the UK follow the US.

In the research by Statista on the 20 leading AI countries in 2023 capacity-wise, the US is number one, followed by China, Singapore, Switzerland, Ireland, and the UK, among others.

When it comes to Bloomberg, the ranking is based on rich nations seen benefiting most from AI. The US is at the top again, followed by Singapore, the UK, Switzerland, and others. China is ranked around 20th.

Despite the differences in rankings and reasoning, one thing is clear: the investment into AI is continuously going up and every country wants to be a part of it. 

Also, an awesome AI workshop coming, free to join 🚀
✔️ https://bit.ly/3w2XQZE
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I share my learning journey here. Join me and let's grow together.

For more on AI and learning materials, please check my previous posts. Alex Wang

#artificialintelligence #generativeai #machinelearning #technology

LLaMA 3 is here! (open source)

It's interesting to see Meta, known for its closed ecosystem, is now leading the charge for open-source AI models on par with GPT-4!

Some impressions that left me after trying it out:

- Faster, faster in everything, faster in delivering simple coding tasks with high quality; faster in image generation.

- Better and more natural results (compared to other popular LLMs) for translation between Chinese and English. According to my friends, it also does a great job translating English to other languages like German & Italian.

- Next-level AI assistant. It can return high-quality recommendations for trips, event planning, etc., with great external knowledge and accurate information. The conversation is super smooth.

- It can do animations and turn them into GIFs for the images you generated; the quality is decent but may not be as good as other specialized AI tools like Midjourney.

If you are a facebook user, here's an extra bonus - you can now access Meta AI right from your Facebook feed - just type your question!

The release of powerful open-source models like LLaMA 3 has the potential to disrupt the AI landscape by putting pressure on closed models to innovate and reduce prices. As a end user, I absolute love it. 

This competition could ultimately drive the development of more advanced, affordable, and accessible AI for everyone.

Have you tried it? Which feature stands out to you the most?
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✔️I share my learning journey here. Join me and let's grow together.

For more on AI and learning materials, please check my previous posts. Alex Wang

#artificialintelligence #chatgpt #technology #machinelearning #datascience

POOJA JAIN

FirstMark Capital has released their annual AI/ML/Data infographics for this year, it's crazy to see how much things have changed!

Back in 2012, the first version of the landscape had 139 companies. Now, the latest version has over 2011 logos - and that's just the bigger brands. There are tons of smaller AI companies out there that haven't even been included yet.

The first landscape was all about big data, which makes sense since there was a decade-long data infrastructure cycle going on. And now we have modern data stack and so much more.

Looking at the latest edition, it's clear that the AI space is heating up. The infographic is packed with companies, showing just how many players have entered the game. And even though we're still in the early stages of AI/ML, a lot of these companies are surprisingly young.

HD version of MAD (ML/AI/Data) landscape 2024 https://lnkd.in/geFypmsx

It's wild to see how much the landscape has changed in just 10 years. What do you think the next 5 years have in store for AI?

#artificialintelligence #datascience #machinelearning #technology

Hippocratic AI and NVIDIA have teamed up to introduce AI nurses for under $9 an hour.

Human nurses have ranked these AI nurses highly in bedside manner and patient education. And on a technical level, they've way outperformed human nurses.

So far, this is voice-only. But last week, an announcement from Microsoft Research may become a game-changer.

Vasa-1 (as attached demos) is an AI system that can generate lifelike, audio-driven talking faces in real-time.

In other words, with only one photo, we can make anyone say anything in real-time.

The controllability of generation is at the next level. The avatars have impressively detailed facial expressions, with blinking, lip and eyebrow expressiveness, and more vivid facial experiences.

The generated video quality is excellent and much more seamless than previous AI systems, with nearly HD resolution (40 frames per second) and negligible starting latency.

What does this mean for us?

We may soon be able to have real-time Zoom calls with next-generation AI models before 2025!

Another part that interested me very much is the potential of social interactions in healthcare, as it mentioned in the paper.

Any potential risk? 100%. Technology itself has no right or wrong; it's up to us to use it responsibly and follow proper regulations.

Demos from Microsoft, edited by SECourses.

Any thoughts on the regulations?
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I share my learning journey here. Join me and let's grow together.

For more on AI and learning materials, please check my previous posts. Alex Wang

#technology #innovation #healthcare  #artificialintelligence

Apple's latest AI model ReALM, is a conversational AI system designed to enhance Siri. 

It might actually make Siri way more functional but use less power and be more capable than any AI we are using today. 

Apple detailed its plan in its paper released a few days ago (the tables in the image are from the paper).

Let's have a quick look at why it is super exciting, and as always, jargon free!✨

ReALM - Reference Resolution As Language Modeling

Reference resolution means understanding what ambiguous phrases like “they”, “that”, “the bottom one”, or “this number onscreen” are referring to. It has been always a hard problem for language models since they are not spatially aware of what's on or behind your screen.

This is where Apple's AI model can truly be a game changer.

This paper is saying, that Apple may find a solution without needing a vision-based AI assistant that can see what's on your screen. It may even use less power, and be used on your phone without having to send your data to a cloud.  

Everything will just be processed within your phone. 

They are trying to find a mobile based voice assistant that understands references to the screen that are natural and behind the screen. 

AI + Siri, on your own smartphone, all the data will be private and secure - there's a huge potential for it. 

*Apple has not released the model or a demo. But the paper provides enough details and the datasets are relatively small, might be possible for researchers to replicate the results. 
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I share my learning journey here. Join me and let's grow together.

For more on AI and learning materials, please check my previous posts. Alex Wang

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