Discover and read the best of Twitter Threads about #machinelearning

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Day 12 of #100DayswithMachineLearning

Topic - Installing Anaconda & Gather Basic Knowledge About these Tools - Jupyter Notebook || Google Colab

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1โƒฃ Anaconda is a distribution of the #Python and R #programming languages for scientific computing (#datascience, #machinelearning applications, large-scale #data processing, predictive analytics, etc.), that aims to simplify package management and #deployment. Image
2โƒฃ The #JupyterNotebook is an open source #web application that you can use to create and share documents that contain live #code, equations, #visualizations, and text. Jupyter #Notebook is maintained by the people at Project Jupyter.

Blog Link - realpython.com/jupyter-noteboโ€ฆ
Read 7 tweets
Day 11 of #100dayswithMachineLearning

Topic : Tensor in Machine Learning

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A tensor is a container which can house data in N #dimensions. Often and erroneously used interchangeably with the matrix (which is specifically a 2-dimensional #tensor), tensors are generalizations of #matrices to N-dimensional space

Tensor notation is much like matrix notation Image
Tensors are more than simply a data container, however. Aside from holding numeric #data, tensors also include descriptions of the valid linear #transformations between tensors. Examples - include the cross product and the dot product.

Blog Link - kdnuggets.com/2018/05/wtf-teโ€ฆ
Read 5 tweets
Day 10 of #100dayswithMachineLearning

Topic - Data Engineer Vs Data Analyst Vs Data Scientist Vs ML Engineer

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Do you want to start a career in the field of #DataScience #MachineLearning but confused about the different job titles available in this Data-Driven career and the appropriate skill sets needed to excel in one

#Data powers today's world ransformed radically by #data @avizyt Image
This article aims to demystify the different job titles for #datascience and #machinelearning based career paths. We would look into some job titles such as #DataAnalyst, Data Scientist, Data Engineer, and Machine Learning #Engineer

Blog Link - medium.com/campusx/explorโ€ฆ
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I recently experimented with OpenAI's API using LangChain. The possibilities of what we can achieve with this technology are truly endless! In this thread, I'll share how I used LangChain to build an app that generates responses to questions based on YouTube video content. Image
First, I extracted the transcript from the videos. For longer videos, I split the document with enough overlap(to ensure continuity), sent the smaller parts to the LLM, got the summary for each part, and combined them for the final result. #OpenAI #LangChain #AI #NLP
Next, I used LangChain's map-rerank method to get the final answer. By tuning the prompts, I was able to generate responses limited to the video's context. #AI #NLP #MachineLearning #ChatGPT
Read 4 tweets
Day9โƒฃ of #100dayswithMachineLearning

Topic - Machine Learning Development Life Cycle

๐Ÿงต
#Machinelearning has given the computer systems the abilities to automatically learn without being explicitly #programmed. But how does a machine learning system work? So, it can be described using the #lifecycle of machine learning.
#Machinelearning life cycle is a cyclic process to build an efficient machine learning #project. The main purpose of the life cycle is to find a solution to the problem or project.

Machine learning life cycle involves seven major steps, which are given below:
#DataScience
Read 6 tweets
" Data Analyst Project on Hotel Booking "

That you can add in your resume or portfolio to showcase your skills ๐Ÿ’ฏ

๐Ÿงต
โ—ป In Recent Year , City Hotel & Resort Hotel have seen High Cancellation Rates. Each Hotel is now Dealing with number of issue as result including Fewer #revenue & Less than ideal Hotel room use.
๐Ÿ”น Insights :

1๏ธโƒฃ More Cancellation occur when prices are higher
2๏ธโƒฃ When there is Longer waiting list , Customer tend to Cancel more frequently
3๏ธโƒฃ The majority of Clients are coming from a offline #travel agents to make their #reservations
Read 6 tweets
SQL Interviews Question for Product companies

๐Ÿ‘‡
create table entries (
name varchar(20),
address varchar(20),
email varchar(20),
floor int,
resources varchar(10));

#SQL #DataScience #DataAnalytics #MachineLearning #Deeplearning
Read 4 tweets
" SQL Interview problem "

๐Ÿงต
This is a REAL SQL Interview question that might seem impossible to solve just by using SQL at first. But during the video the problem by breaking it into multiple parts

#SQL #DataScience #DataCleaningchallenge #DataAnalytics #dataviz #MachineLearning #deeplearning
Youtube Video Link -
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Live from #GartnerDA | The Future of Data Science and Machine Learning: Critical Trends You Can't Ignore with Svetlana Sicular, Gartner VP Analyst: gtnr.it/3JOkYPF Image
About this session: Understanding key trends influencing the future of #ML and #DataScience is key for modern enterprise success. Svetlana shares how leaders should plan for future #AI initiatives and improve their current AI solutions: gtnr.it/3JOkYPF #GartnerDA
#DataScience and #ML is shifting from custom-tailored to ready-to-wear. The fields are going from exactly fitting the business to needing customization for each business function. #GartnerDA Image
Read 14 tweets
Day8โƒฃ of #100dayswithMachineLearning

Topic - Applications of Machine learning

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#Machinelearning is a buzzword for today's #technology it is growing very rapidly day by day. We are using machine learning in our daily life even without knowing it such as @Google Maps, Google assistant, #Alexa, etc. Below are some most trending real-world applications of ML Image
โœ… Image Recognition:
It is one of the most common applications of machine learning. It is used to identify objects, persons, places, #digital images, etc. The popular use case of image recognition and face detection is Automatic friend tagging suggestion

javatpoint.com/applications-oโ€ฆ
Read 5 tweets
" SQL Puzzle Interview Question "

๐Ÿงต
Table script:

create table input (
id int,
formula varchar(10),
value int
)
insert into input values (1,'1+4',10),(2,'2+1',5),(3,'3-2',40),(4,'4-1',20);
Read 4 tweets
" Exploratory Data Analysis on Terrorism "

๐Ÿงต
We are performed Exploratory Data Analysis on terrorism #dataset to find out the hot zone of #terrorism. #EDA nothing but #analyzing the given data & finding the #trends, patterns & making some assumptions. #DataVisualization #DataScience #MachineLearning
In this #dataset, there are many features including countries, states, regions, gang names, weapon types, target types, years, months, days, and many more features.
Read 8 tweets
Day7โƒฃ of #100dayswithMachinelearning

Topic - Challenges in Machine Learning

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The model will not perform well if training data is small, or noisy with errors outlier or if #data is not representative consist of irrelevant feature(garbage in garbage out) lastly neither too simple(result in #underfitting) nor too complex(results in #overfitting

#DataScience Image
Not enough training data.
Poor Quality of data.
Irrelevant features.
Nonrepresentative training data.
Overfitting and Underfitting.

#DataCleaningchallenge #MachineLearning #Deeplearning #DataAnalytics #DataVisualization #Python #Powerbi #SQL #MYSQL
analyticsvidhya.com/blog/2021/06/5โ€ฆ
Read 5 tweets
๐Ÿš€๐Ÿง  Thread: Unlock the Power of GPT & LLMs ๐Ÿง ๐Ÿš€

1/ As a huge fan of ChatGPT, I am thrilled to share my insights on how to make the most out of Generative Pre-trained Transformers (GPT) and Large Language Models (LLMs) in this THREAD. Get ready for the future of AI! ๐Ÿ”ฅ๐ŸŒ
2/ First things first, brush up on the basics! GPT and LLMs use @OpenAIโ€™s transformers framework to comprehend & generate human-like text. Want to dive deeper into it? Check out their whitepaper๐Ÿ‘ฉโ€๐Ÿ’ป๐Ÿ‘จโ€๐Ÿ’ป: research.openai.com/blog/ #MachineLearning #NaturalLanguageProcessing
3/ GPT and LLMs have a wide range of applications! They can be used for:

- Writing content ๐Ÿ–Š๏ธ
- Generating code ๐Ÿ’ป
- Conversational AI ๐Ÿค–
- Language translation ๐ŸŒ And so much more! In short, they are shaping the AI world as we know it! โšก๏ธ #RealWorldApplications
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#ChiefJusticeofIndia DY Chandrachud to deliver a talk at the @IndiaToday Conclave on 'Justice in the Balance: My idea of India. And the importance of separation of powers in a democracy'.

#SupremeCourt #SupremeCourtofIndia #CJI Image
On pendency, #CJI DY Chandrachud says, "We need greater efficiency...judge to population ratio skewed, lack of infrastructure in district judiciary main reasons."

#SupremeCourt #SupremeCourtofIndia Image
#CJI DY Chandrachud: Our judiciary is based on the colonial idea that people have to access justice. But it must now give way to the idea of justice as an essential service that we must provide to our citizens.

#SupremeCourt #SupremeCourtofIndia
Read 8 tweets
What is a correct Data Engineering Learning Path?

My thoughts in the ๐Ÿงต

#Data #DataEngineering #MLOps #MachineLearning #DataScience
I believe that the following is a correct order to start in ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐——๐—ฎ๐˜๐—ฎ ๐—˜๐—ป๐—ด๐—ถ๐—ป๐—ฒ๐—ฒ๐—ฟ๐—ถ๐—ป๐—ด ๐—ฃ๐—ฎ๐˜๐—ต:

๐Ÿ‘‡
โžก๏ธ ๐—จ๐—ป๐—ฑ๐—ฒ๐—ฟ๐˜€๐˜๐—ฎ๐—ป๐—ฑ ๐—•๐—ฎ๐˜€๐—ถ๐—ฐ ๐—ฃ๐—ฟ๐—ผ๐—ฐ๐—ฒ๐˜€๐˜€๐—ฒ๐˜€:

๐Ÿ‘‰ Data Extraction
๐Ÿ‘‰ Data Validation
๐Ÿ‘‰ Data Contracts
๐Ÿ‘‰ Loading Data into a DWH / Data Lake
๐Ÿ‘‰ Transformations in a DWH / Data Lake
๐Ÿ‘‰ Scheduling

๐Ÿ‘‡
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What are the basics of Writing Data to a Kafka Topic?

๐Ÿงต

#Data #DataEngineering #MLOps #MachineLearning #DataScience
Kafka is an extremely important ๐——๐—ถ๐˜€๐˜๐—ฟ๐—ถ๐—ฏ๐˜‚๐˜๐—ฒ๐—ฑ ๐— ๐—ฒ๐˜€๐˜€๐—ฎ๐—ด๐—ถ๐—ป๐—ด ๐—ฆ๐˜†๐˜€๐˜๐—ฒ๐—บ to understand as it was the first of its kind and most of the new products are built on the ideas of Kafka.

๐—ฆ๐—ผ๐—บ๐—ฒ ๐—ด๐—ฒ๐—ป๐—ฒ๐—ฟ๐—ฎ๐—น ๐—ฑ๐—ฒ๐—ณ๐—ถ๐—ป๐—ถ๐˜๐—ถ๐—ผ๐—ป๐˜€:

๐Ÿ‘‡
โžก๏ธ Clients writing to Kafka are called ๐—ฃ๐—ฟ๐—ผ๐—ฑ๐˜‚๐—ฐ๐—ฒ๐—ฟ๐˜€,
โžก๏ธ Clients reading the Data are called ๐—–๐—ผ๐—ป๐˜€๐˜‚๐—บ๐—ฒ๐—ฟ๐˜€.
โžก๏ธ Data is written into ๐—ง๐—ผ๐—ฝ๐—ถ๐—ฐ๐˜€ that can be compared to ๐—ง๐—ฎ๐—ฏ๐—น๐—ฒ๐˜€ ๐—ถ๐—ป ๐——๐—ฎ๐˜๐—ฎ๐—ฏ๐—ฎ๐˜€๐—ฒ๐˜€.

๐Ÿ‘‡
Read 8 tweets
๐Ÿ‘‰ "MAT: Mask-Aware Transformer for Large Hole Image Inpainting" proposes a new method for image inpainting using the Mask-Aware Transformer neural network architecture. It generates high-quality and visually consistent inpainting results for images with large holes.
๐Ÿ‘‰ DALL-E can also be used for inpainting. By adding frames, the scene can be extended and the prompt can be switched up to create something new and surreal. It's like painting your own dreamscape or designing your own world.
๐Ÿ‘‰ The results from DALL-E are often surreal and dreamlike, making it fun and exciting to use. Check out the video and examples for some creative ways to outpaint.
Read 5 tweets
So what is the difference between Row Based and Column Based file formats?

๐Ÿงต

#Data #DataEngineering #MLOps #MachineLearning
๐—ฅ๐—ผ๐˜„ ๐—•๐—ฎ๐˜€๐—ฒ๐—ฑ:

โžก๏ธ Rows on disk are stored in sequence.
โžก๏ธ New rows are written efficiently since you can write the entire row at once.

๐Ÿ‘‡
โžก๏ธ For select statements that target a subset of columns, reading is slower since you need to scan all sets of rows to retrieve one of the columns.

๐Ÿ‘‡
Read 8 tweets
What are the main use cases for Apache Kafka or any other Distributed Messaging System?

๐Ÿงต

#Data #DataEngineering #MLOps #MachineLearning #DataScience Image
We have covered lots of concepts around Kafka already. But what are the most common use cases for The System that you are very likely to run into as a Data Engineer?

๐—Ÿ๐—ฒ๐˜โ€™๐˜€ ๐˜๐—ฎ๐—ธ๐—ฒ ๐—ฎ ๐—ฐ๐—น๐—ผ๐˜€๐—ฒ๐—ฟ ๐—น๐—ผ๐—ผ๐—ธ:

๐Ÿ‘‡
๐—ช๐—ฒ๐—ฏ๐˜€๐—ถ๐˜๐—ฒ ๐—”๐—ฐ๐˜๐—ถ๐˜ƒ๐—ถ๐˜๐˜† ๐—ง๐—ฟ๐—ฎ๐—ฐ๐—ธ๐—ถ๐—ป๐—ด.

โžก๏ธ The Original use case for Kafka by LinkedIn.
โžก๏ธ Events happening in the website like page views, conversions etc. are sent via a Gateway and piped to Kafka Topics.

๐Ÿ‘‡
Read 12 tweets
SQL JOINS for beginners { Must Read }

Joins are the most fundamental concepts in SQL and having a clear understanding of Joins is very essential to write good SQL queries.

๐Ÿงต
Topics -

โœ…What are JOINS in SQL
โœ…Inner Joins in SQL
โœ…Left Join in SQL
โœ…Right Join in SQL

โœ…FULL OUTER JOIN in SQL
โœ… CROSS JOIN in SQL
โœ… NATURAL JOIN in SQL
โœ… SELF JOIN in SQL

Read 5 tweets
๐Ÿ“ท "Is Insta dead?" This is the question on many people's minds after tech mogul Elon Musk recently tweeted this... Image
๐Ÿค– "Will AI Replace Artists?" This is another question that's been buzzing around the art world lately. A recent headline claimed that an Instagram photographer with nearly 29,000 followers since October had admitted that his stunning portraits were all AI-generated.
This begs the question - if AI can produce artwork that is indistinguishable from human-generated work, what does the future hold for artists?
Read 7 tweets
Roadmap to becoming Data Analyst in three months absolutely free. No need to pay a penny for this.

I have mentioned a roadmap with free resources.

A thread๐Ÿงต๐Ÿ‘‡
1. First Month Foundations of Data Analysis

A. Corey Schafer - Python Tutorials for Beginners:
B. StatQuest with Josh Starmer - Statistics Fundamentals:
C. Ken Jee - Data Analysis with Python
2. Second Month - Advanced Data Analysis Techniques

A. Sentdex - Machine Learning with Python
B. StatQuest with Josh Starmer - Machine Learning Fundamentals
C. Brandon Foltz - Business Analytics
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"China military modernization... is really just kind of awesome" @DefenseIntel #China Mission Group Chief Doug Wade warns @INSAlliance

"It's the totality of how the pull [all the modernization efforts] together that's the most impressive aspect"
Any move by #China on #Taiwan would be preceded by a range of activities, including #cyber activity, blockades, more violations of Taiwanese airspace & military measures short of putting troops on the ground, per @DefenseIntel's Wade
#China's Xi Jinping does not prefer to use force for unification w/#Taiwan - "China doesn't want to start a fight" per @DefenseIntel's Wade

But he cautions, "They haven't ruled it out"
Read 9 tweets

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