arxiv.org/abs/2104.10350 -- a detailed study of CO2 emission in large models from Google

A visual introduction to machine learning

http://www.r2d3.us/visual-intro-to-machine-learning-part-1/

Best view in desktop 🖥

Join in their team If you are interested for part3 launch 🚀

What salaries does a data science professional earn?
The base annual pay for a data scientist in the US is USD 117,345, with a range of USD 86,000–157,000 (source: Glassdoor).

Here is a look at estimated salaries for data scientists by experience level (source: ZipRecruiter):
👉Entry level: The annual salary is estimated at USD 69,000.
👉Mid-level: The median annual salary is USD 89,000.
👉Experienced: These are professionals with extensive experience in their data science careers. They could earn median annual salaries of USD 1,28,000.
👉Experienced at manager level: The median annual salary could be as high as USD 184,000.

Estimated annual salaries:
👉In India: INR 708,012 (approx USD 9,507, source: PayScale)
👉In the US: USD 96,106 (source: PayScale)

Tesla uses advanced AI for vision and planning, supported by efficient use of inference hardware to make Autopilot to full self-driving. A full build of Tesla's Autopilot neural networks (Deep leaning Model ) involves 48 networks that take 70,000 GPU hours to train.

AI features in Tesla.
1. AI integrated chips
2. Autopilot

⚡️⚡️⚡️Professor 👨‍🏫 at University Of Washington stated that 👇



2000s: Neural networks = Deep learning.
2010s: Machine learning = Deep learning.
2020s: Artificial intelligence = Deep learning.
2030s: Computer science = Deep learning.
2040s: Science = Deep learning.
2050s: The universe = Deep learning.


Your learning never going to be wasted .. 💪💪

IIT Madras Team Develop AI To Restore Old, Damaged Photos To New.

Researchers from IIT Madras have harnessed the power of artificial neural networks to restore CCTV images that have been degraded due to weather conditions, beyond recognition.

Paper published in IEEE.
Degradation Aware Approach to Image Restoration Using Knowledge Distillation
https://ieeexplore.ieee.org/document/9288928/authors#authors

But you know that fundamentally they are not the same. Statistics is about doing "tests" and calculating the probability of errors of the 2 types. Data science is about manipulating the data before they can be submitted to a statistical analysis.

Understanding algorithmic paradigms helps in becoming an efficient problem solver with code, and acing, and success in coding interviews.

Sharing a highly resourceful, and amazing repository with 100s of implemented algorithms in Python.                                                                                                                                                           
The implementations range from data structures to compression machine learning algorithms.



https://the-algorithms.com/

Feature Selection Techniques - Extended Overview in One Picture


Source - LinkedIn Post

By - AI Bot 🤖

AWS - Increasing amount of GUI-based data transformation and machine learning tools;

Microsoft Azure - A point-and-click visual interface for machine learning, “data preparation, feature engineering, training algorithms, and model evaluation”;

Google Cloud Platform - similar functionality as part of their Cloud AutoML offering.


What about Oracle?

Oracle is also reducing the total cost of ownership with elastic scaling and auto-scaling for changing workloads

A serious bottleneck to data work delivering business value across industries is the amount of expertise required at many steps along the data pipeline.

Oracle Autonomous Data Warehouse competes with incumbent products including
Amazon Redshift,
Azure Synapse,
Google BigQuery,
and Snowflake.

RLCard: A Toolkit for Reinforcement Learning in Card Games


The goal of RLCard is to bridge reinforcement learning and imperfect information games.

New in 🤗datasets v1.9:
⬇️ Dataset Streaming
🤯 Huge datasets like C4 and mC4
🔥 JAX integration
💽 Parquet support

Stream terabytes of data at high speed in a few lines of code !

https://t.co/wsen9sLzp6?amp=1

The PyData Global conference is an online event where users, contributors, developers, and newcomers of data analysis tools from around the world can share experiences to learn from one another and grow together. This three-day event will consist of talks, tutorials, and discussions to bring attendees the latest project features along with cutting edge use cases.


last year’s inaugural online event that had 2,000 attendees


https://pydata.org/global2021/


The Call for Proposals is open with the deadline to submit August 15.

I am planning to deliver Azure ML concepts tomorrow. It is going to be 2 hour session. Interested people can join. I will share link and timings by evening.

tqdm is a Python library that allows you to output a smart progress bar by wrapping around any iterable. A tqdm progress bar not only shows you how much time has elapsed, but also shows the estimated time remaining for the iterable.

tqdm derives from the Arabic word taqaddum (تقدّم) which can mean "progress," and is an abbreviation for "I love you so much" in Spanish (te quiero demasiado).
Instantly make your loops show a smart progress meter - just wrap any iterable with tqdm(iterable), and you're done!

Pyflyby is a set of Python programming productivity tools for Python 2.7 and 3.7+.

$ pip install pyflyby

For command-line interaction:
• py: command-line multitool

for more : https://github.com/deshaw/pyflyby

What’s New In Python 3.11
Next year Python’s version 2022

1. Enhanced error locations in tracebacks
2. Add math.cbrt(): return the cube root of x. (Contributed by Ajith Ramachandran in bpo-44357.)
3. On Windows, os.urandom() uses BCryptGenRandom() instead of CryptGenRandom() which is deprecated.
4. smtpd.MailmanProxy is now removed as it is unusable without an external module, mailman