Discover and read the best of Twitter Threads about #datascience
Most recents (24)
📢 Learn bioinformatics on your own, online 💻, for free, any time, any place 🌎 with the @ISBSIB e-learning courses!
👉 sib.swiss/training/e-lea…
#Training #lifesciences
👉 sib.swiss/training/e-lea…
#Training #lifesciences
From UNIX programming for beginners
👉 sib.swiss/training/cours…
#Training #lifesciences #bioinformatics
👉 sib.swiss/training/cours…
#Training #lifesciences #bioinformatics
to exploring and visualizing your data with #Python!
👉 sib.swiss/training/cours…
#Training #DataScience #dataviz
👉 sib.swiss/training/cours…
#Training #DataScience #dataviz
✅Linear Neural Networks for Regression and Classification explained in simple terms and how to use it (with code).
A quick thread 🧵👇🏻
#Python #DataScience #MachineLearning #DataScientist #Programming #Coding #100DaysofCode #hubofml #deeplearning
Pic credits : Joshua
A quick thread 🧵👇🏻
#Python #DataScience #MachineLearning #DataScientist #Programming #Coding #100DaysofCode #hubofml #deeplearning
Pic credits : Joshua
1/ Imagine you have a box with a lot of buttons on it, and each button can give you a different answer. You also have a big list of questions that you want to ask, like "What's the weather like today?" or "Is this a cat or a dog?".
2/ Now, instead of asking just one button at a time, you can connect all the buttons together with wires. When you ask a question, it goes through the wires and each button can help decide the answer a little bit.
Have you heard about Otter: A Multi-Modal AI Model with In-Context Instruction Tuning? This cutting-edge model leverages a large-scale dataset called MIMIC-IT to achieve state-of-the-art performances in perception and reasoning benchmarks. @Microsoft @NTUsg #AI
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🤖 Otter is not your average AI model. With 2.8 million multimodal instruction-response pairs, Otter demonstrates remarkable proficiency in multi-modal perception, reasoning, and in-context learning. It effectively aligns with the user's intentions. #MultiModal #AI
📈 The MIMIC-IT dataset, instruction-response collection pipeline, benchmarks, and the Otter model are all available for use. This means that Otter can be applied to a variety of industries, from healthcare to finance, to improve perception, reasoning, and planning. #DataScience
The Crucial Role of Data Science in Football ⚽️📊
🧵 ⬇️
🧵 ⬇️
Data science has revolutionized the world of football! From player performance analysis to team strategies, it has become an indispensable tool for clubs and coaches. Let's dive into how crucial data science is in shaping the beautiful game. #FootballAnalytics #DataScience(1)
In football, data science helps teams make informed decisions during player recruitment. By analyzing vast amounts of data, clubs can identify talented individuals, assess their playing style, and determine how they would fit within the team's tactics. #RecruitmentInsights (2)
Ahoy #oceaners 👋
I thought to make all of your weekend more fun and exciting , so, The 2nd part of the @oceanprotocol megathread is here !
Grab an espresso or cappuccino or whatever drink you prefer and enjoy the beauty of what $ocean has created .
#web3 #AI #DataScience
I thought to make all of your weekend more fun and exciting , so, The 2nd part of the @oceanprotocol megathread is here !
Grab an espresso or cappuccino or whatever drink you prefer and enjoy the beauty of what $ocean has created .
#web3 #AI #DataScience
In the previous megathread , I explained why we need to actually share data as it will bring a lot of value to humanity and lead to an acceleration in advancement of #AI . I also explained the glorious $ocean data market and how beautifully the way it functions .
I solely don't believe in this, even the World economic forum praised the work of @oceanprotocol by awarding them with the World economic forum Technology pioneer award and we also have big organisations like German central bank, @Unilever , Daimler-Mercedes Benz Singapore ...
✅Time Series Forecasting explained in simple terms and how to use it ( with code).
A quick thread 🧵👇🏻
#Python #DataScience #MachineLearning #DataScientist #Programming #Coding #100DaysofCode #hubofml #deeplearning
Pic credits : ResearchGate
A quick thread 🧵👇🏻
#Python #DataScience #MachineLearning #DataScientist #Programming #Coding #100DaysofCode #hubofml #deeplearning
Pic credits : ResearchGate
1/ Imagine you have a special notebook where you write down the temperature outside every day. You write down the temperature in the morning and also in the afternoon. Now, after a few months, you have a lot of temperature numbers in your notebook.
2/ Time series forecasting is like using magic to predict what the temperature might be in the future. You look at all the numbers you wrote down and try to find a pattern or a trend.
So… this is a thread and a good one… I stopped by #Silhouette in Greenwood to visit with an amazing founder Venita Cooper to talk about milestones and their current focus as part of @devlandnext’s program with Build in Tulsa, called Grow Tulsa. But wait there is more…
I learned there that Coop would be presenting at the Showcase hosted by @lightshipcap to bring attention to a few of the amazing companies that went through their accelerator. She was definitely nervous but her new company #arbit is gaining traction, so there is plenty to talk… twitter.com/i/web/status/1…
I had let @BrianBrackeen know I would be in attendance earlier that week on Twitter. But I’m sure he didn’t know what to expect.
🚨🤖📈 Exciting news! Sequoia just dropped a study on the Language Model Stack, and it shows rapid growth in AI applications. 🤯
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📊 The study shows that nearly every company in the Sequoia network is building language models into their products, with 65% already in production. #sequoia #languagemodelstack
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✅Generative Adversarial Networks ( GANs) explained in simple terms and how to use it ( with code).
A quick thread 🧵👇🏻
#Python #DataScience #MachineLearning #DataScientist #Programming #Coding #100DaysofCode #hubofml #deeplearning
Pic credits : ResearchGate
A quick thread 🧵👇🏻
#Python #DataScience #MachineLearning #DataScientist #Programming #Coding #100DaysofCode #hubofml #deeplearning
Pic credits : ResearchGate
1/ Imagine you have two friends, let's call them the "artist" and the "critic." The artist wants to draw something cool, and the critic wants to judge if the drawing is good or not. The artist tries to draw something, and the critic looks at it and says whether it's good or bad.
2/ Now, the artist really wants to improve, so they keep drawing and the critic keeps judging. Over time, the artist gets better and better at drawing because they learn from the critic's feedback. The artist wants to make drawings that the critic will say are really amazing!
🧵 Exciting Apps You Can Build with @LangChainAI by @hwchase17
Have you ever thought about the possibilities offered by LangChain?
Let's dive into five amazing app ideas you can bring to life using this versatile tool and get access to code!
#AI #ChatGPT
Have you ever thought about the possibilities offered by LangChain?
Let's dive into five amazing app ideas you can bring to life using this versatile tool and get access to code!
#AI #ChatGPT
First up, a context-aware Chatbot! 🤖
Harness the power of natural language processing to create a chatbot that delivers contextual and relevant answers to user queries. The integration of additional data sources can make your bot!
Repo: tinyurl.com/4y9rt92j
#LangChain
Harness the power of natural language processing to create a chatbot that delivers contextual and relevant answers to user queries. The integration of additional data sources can make your bot!
Repo: tinyurl.com/4y9rt92j
#LangChain
Ever drowned in lengthy documents? Here's a solution - A SummarizationApp! 📃
LangChain can help you condense long articles or documents while preserving their core meaning, making it easier to absorb information. #AI
github.com/ncodepro/pdfch…
LangChain can help you condense long articles or documents while preserving their core meaning, making it easier to absorb information. #AI
github.com/ncodepro/pdfch…
A few days back, 2 Data Analyst newbies showed me mistakes they encountered during their analysis process. It dawned on me that lots of times, we don't diligently follow through the data analysis process, especially the cleaning phase.
In this short🧵, I break down this process.
In this short🧵, I break down this process.
PHASE 1: ASK QUESTIONS
The first step in the analysis process is to formulate a problem to solve or a question to answer, such as: are customers aged 21 to 30 more likely to churn than customers aged 41 to 50? As analysts, we must be very curious, we must ASK QUESTIONS!
The first step in the analysis process is to formulate a problem to solve or a question to answer, such as: are customers aged 21 to 30 more likely to churn than customers aged 41 to 50? As analysts, we must be very curious, we must ASK QUESTIONS!
PHASE 2: Collect & Store Data
Next, we need to collect and store the necessary data, which could require the use of a database or a spreadsheet. For large datasets, we store them in a database. For datasets shy of a million records, spreadsheet software like Excel can be used.
Next, we need to collect and store the necessary data, which could require the use of a database or a spreadsheet. For large datasets, we store them in a database. For datasets shy of a million records, spreadsheet software like Excel can be used.
I've been experimenting with #chatgpt for #datascience for 16 weeks.
And I now have a process I'm happy with.
Here are the details. 🧵
#datascience #rstats
And I now have a process I'm happy with.
Here are the details. 🧵
#datascience #rstats
Using ChatGPT for data science has been a MASSIVE learning curve.
I began using it for complex workflows.
And I FAILED miserably.
I began using it for complex workflows.
And I FAILED miserably.
Case in point- My first try was asking it to build me a machine learning model + a shiny app for scoring customers.
FAIL.
My ask was just too complex.
FAIL.
My ask was just too complex.
This is coming from a person that has created two R packages that combine for 1.5 Million downloads.
Has trained elite data scientists at Apple, Walmart, Google.
And has built a career teaching students how to become data scientists.
Why did it take so long?
Has trained elite data scientists at Apple, Walmart, Google.
And has built a career teaching students how to become data scientists.
Why did it take so long?
👉 Too many resources.
I thought I had to learn everything:
Deep learning.
Machine learning.
Algorithms.
The toughest part was figuring out which tools to learn and which were “red herrings” (a waste of time).
I thought I had to learn everything:
Deep learning.
Machine learning.
Algorithms.
The toughest part was figuring out which tools to learn and which were “red herrings” (a waste of time).
There are over 2,000 AI tools that have hit the market over the last 365 days.
So I condensed them into the best.
Here are the TOP 15 AI TOOLS for Data Scientists. 🧵
#datascience #rstats #python #career #ai
So I condensed them into the best.
Here are the TOP 15 AI TOOLS for Data Scientists. 🧵
#datascience #rstats #python #career #ai
It's hard not to get excited about #AI. The potential is insane. It's also scary.
And the worst thing you can do for your career is ignore AI.
I mean, there are literally 2,000 new tools that have hit the market in 365 days. So where do you start?
I want to help.
And the worst thing you can do for your career is ignore AI.
I mean, there are literally 2,000 new tools that have hit the market in 365 days. So where do you start?
I want to help.
Here are the 15 AI tools that, as a data scientist, MUST be on your radar (I'm road-testing ALL of these).
CODE:
1. ChatGPT: OpenAI's AI Chatbot openai.com/blog/chatgpt
CODE:
1. ChatGPT: OpenAI's AI Chatbot openai.com/blog/chatgpt
3 battle-tested skills that every data scientist should have.
(and how to apply them to a job interview)🧵
#datascience #skills #rstats #python
(and how to apply them to a job interview)🧵
#datascience #skills #rstats #python
People don’t realize this but I was a data science consultant and corporate trainer...
That was long before I was a “teacher” and a “6-figure data science mentor”.
That’s where I learned these skills through battle-testing.
And my clients were my test subjects. 🧪🧑🔬
That was long before I was a “teacher” and a “6-figure data science mentor”.
That’s where I learned these skills through battle-testing.
And my clients were my test subjects. 🧪🧑🔬
1. Focus on results
Outcomes are what moves mountains. Not analysis.
Yes- data analysis is incredibly important.
But, what’s more important is what you and your company do with the analysis.
Outcomes are what moves mountains. Not analysis.
Yes- data analysis is incredibly important.
But, what’s more important is what you and your company do with the analysis.
“Why python vs R?”
“What’s inside your new python course?”
“What will it do for me (if I’m an #R user)?”
I’ve been getting a ton of questions so I figured Twitter can help me explain.
#python #rstats #datascience
“What’s inside your new python course?”
“What will it do for me (if I’m an #R user)?”
I’ve been getting a ton of questions so I figured Twitter can help me explain.
#python #rstats #datascience
1. R vs Python.
My guess is 90% of my followers use R.
So why am I promoting python?
Well I just wrote a full article on why R users should learn **some** Python…
Even if python is harder.
business-science.io/code-tools/202…
My guess is 90% of my followers use R.
So why am I promoting python?
Well I just wrote a full article on why R users should learn **some** Python…
Even if python is harder.
business-science.io/code-tools/202…
2. What’s inside my new python course?
I just put together a 5 minute video that shows one powerful use case for python.
And it’s the course project.
I just put together a 5 minute video that shows one powerful use case for python.
And it’s the course project.
ChatGPT just made a Data Science Web App for me in under 15 minutes.
Here's the story. 🧵
#datascience #rstats
Here's the story. 🧵
#datascience #rstats
1. Machine Learning
ChatGPT created the basic code for an XGBoost Machine Learning model
The model is used for scoring the customer spend
ChatGPT created the basic code for an XGBoost Machine Learning model
The model is used for scoring the customer spend
2. Shiny App
ChatGPT produced the code for a basic shiny app that packages the model...
...And the app can make new spend predictions based on tweaking inputs for a new customer.
ChatGPT produced the code for a basic shiny app that packages the model...
...And the app can make new spend predictions based on tweaking inputs for a new customer.
I just revealed the data science project that helped my small business generate $3,500,000 in revenue in the last 2 years.
Here are the juicy details...
#datascience #python #rstats #career
Here are the juicy details...
#datascience #python #rstats #career
It's true. My company did almost $2,000,000 last year with an email list size of under 100,000.
And a big part of it was the Marketing Analytics that I'm revealing in my new Python course.
What did we do?
And a big part of it was the Marketing Analytics that I'm revealing in my new Python course.
What did we do?
We used machine learning to score leads.
We then created nature vs sales targeting segments.
Then we did this...
We then created nature vs sales targeting segments.
Then we did this...
The basics of R to Advance for Beginners.
Bookmark this Tweet and Follow me
COMMENT PDF - and I will send you the compiled PDF of more than 10 Cheat Sheets
If your inbox is disabled please DM me.
#DataAnalytics #DataScience #rstats #data #BigData
Bookmark this Tweet and Follow me
COMMENT PDF - and I will send you the compiled PDF of more than 10 Cheat Sheets
If your inbox is disabled please DM me.
#DataAnalytics #DataScience #rstats #data #BigData
1/20
2/20
Hello Datafam,
So someone asked me where they can get to practice SQL so I would dropping links to platforms where you can practice SQL
Thread 🧵
So someone asked me where they can get to practice SQL so I would dropping links to platforms where you can practice SQL
Thread 🧵
1) Hackerrank @hackerrank
I have used this platform and I really loved using it. I also love that they reward with badges and stars as you make progress
check it out here: hackerrank.com/domains/sql
I have used this platform and I really loved using it. I also love that they reward with badges and stars as you make progress
check it out here: hackerrank.com/domains/sql
2) DataLemur @DataLemurHQ
I personally love this because they give standard interview questions that cuts across various industries. There are also level such as Easy, Medium and Hard so if you want to prepare for technical interviews, check it out
datalemur.com/sql-interview-…
I personally love this because they give standard interview questions that cuts across various industries. There are also level such as Easy, Medium and Hard so if you want to prepare for technical interviews, check it out
datalemur.com/sql-interview-…
90% of data scientists don't track their experiments.
Here's how to fix that with one line of code... 🧵
#datascience
Here's how to fix that with one line of code... 🧵
#datascience
Experiments are the lifeblood of a data scientist.
They help you answer questions like:
Which model performed best?
Which model is actively deployed?
When is the last time we updated the model?
But 90% of data scientist are just saving a model file and thinking their finished
They help you answer questions like:
Which model performed best?
Which model is actively deployed?
When is the last time we updated the model?
But 90% of data scientist are just saving a model file and thinking their finished
Happy Sunday Everyone,
I think I am feeling well enough to make this tweet
So I want to share a small win here. I am participating in the Data Analytics Super League organized by @lighthall_co and I want to share that I advanced to level 3 in flying colors
Top of the table😁
I think I am feeling well enough to make this tweet
So I want to share a small win here. I am participating in the Data Analytics Super League organized by @lighthall_co and I want to share that I advanced to level 3 in flying colors
Top of the table😁
The Level 2 challenge was a murder mystery challenge to find who the killer is and we were to solve the challenge using SQL
If you dug deeper you'd find out that there was someone who hired it.
Nothing complex but it was fun, felt like a detective 😊
If you dug deeper you'd find out that there was someone who hired it.
Nothing complex but it was fun, felt like a detective 😊
My submission: drive.google.com/drive/folders/…
If you want to try it out yourself and have fun with SQL, check here
lighthall.co/challenge/cd01…
Thank you @lighthall_co and @thenaijacarguy for the challenge
it is getting really interesting and level 3 is not easy
If you want to try it out yourself and have fun with SQL, check here
lighthall.co/challenge/cd01…
Thank you @lighthall_co and @thenaijacarguy for the challenge
it is getting really interesting and level 3 is not easy
The basics of R for Beginners.
Bookmark this Tweet and Follow for More
COMMENT PDF - and I will send you the compiled PDF of more than 10 Cheat Sheets
#DataAnalytics #DataScience #rstats #data #BigData
Bookmark this Tweet and Follow for More
COMMENT PDF - and I will send you the compiled PDF of more than 10 Cheat Sheets
#DataAnalytics #DataScience #rstats #data #BigData
If you have not received any DM from me that means your Inbox is disabled.
Follow me so that I can Inbox you.
Follow me so that I can Inbox you.
Don't forget to:
✅ Follow
@dr_abdulali125
🔥
✅Like the first tweet in the thread
✅ Retweet this post to share with the world.
Have an amazing day 🙏
✅ Follow
@dr_abdulali125
🔥
✅Like the first tweet in the thread
✅ Retweet this post to share with the world.
Have an amazing day 🙏
As a data scientist, productivity is a 10X super power.
Here's a short list of AI tools to help data scientists with: 🧵
#ai #datascience #career #skills #tools
Here's a short list of AI tools to help data scientists with: 🧵
#ai #datascience #career #skills #tools
1. Writing code
AI pair programming is a huge benefit.
Tools like #chatgpt & github #copilot can help debug complex code and replace Googling + Stack Overflowing for common scripting.
Key skill: ChatGPT prompting (more on this in my free ChatGPT for Data Scientists)
AI pair programming is a huge benefit.
Tools like #chatgpt & github #copilot can help debug complex code and replace Googling + Stack Overflowing for common scripting.
Key skill: ChatGPT prompting (more on this in my free ChatGPT for Data Scientists)
2. Code Quality & Documentation
Great products have great documentation. AI can help produce documentation, comment code, and replace time-consuming manual documentation with automated AI docs.
Key Skill: Using @mintlify to build your docs: mintlify.com
Great products have great documentation. AI can help produce documentation, comment code, and replace time-consuming manual documentation with automated AI docs.
Key Skill: Using @mintlify to build your docs: mintlify.com
