The Dispatch - Continuous Learning with ADaSci
ADaSci
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ADaSci is committed to upskilling and reskilling data science community members. With this aim, we provide a range of highly curated learning resources under?Continuous Learning. You will find here learning materials related to important areas of data science and machine learning, including video tutorials, reference materials, python notebooks, etc. Most of these resources are available for free for ADaSci members.
In the row of upskilling, recently, we conducted two workshops:?Statistics with Python for Data Science Beginners?and?Linear Algebra with Python for Data Science. The workshop recordings and reference materials are available in the Continuous Learning section.
ADaSci has also started Ad-hoc training for corporates and other organizations in data science and relevant areas. Organizations can upskill or reskill their team with cutting-edge and on-demand data science skills by the leading industry experts of the global professional data science body. The member organizations can avail of cost benefits in ad-hoc training.?
We also have some curated dosage this week to update you on the latest developments in the data science field.?
Top Stories
Read this annual data science and AI trends report by Analytics India Magazine that aims to highlight the top trends that will define the industry in the year 2023.
Despite being battered in the stock market, Apple had an interesting year in 2022. Read the achievements which put Apple ahead of Meta and Google in 2022.
Check out the list of top datasets and projects that were open-sourced in 2022 for further contributions and development.
Muse claims to be faster as it uses a compressed, discrete latent space and parallel decoding. Check out the article for complete details
领英推荐
Considering the advancements and developments in computer vision, look at some of the predictable trends in this field.
Developers Dosage
Heuristic and metaheuristic-based algorithms play a vital role by suitably optimizing AI agents to produce accurate and reliable results. Understand these techniques in detail.?
When determining the effectiveness of a classification algorithm, it can be difficult to decide which metric to use: AUC-ROC or Accuracy. Get a complete understanding here.
Load balancing approaches distribute the workload among multiple machines or services within cloud infrastructure to handle user requests effectively. Learn more about this approach.?
SK-Learn provides features to automate data preprocessing and model-building steps together using pipelines. Learn more about using these pipelines.?
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We are always open to hearing from our members regarding their feedback and expectations from ADaSci. We will try our best to incorporate valuable suggestions from the members. Please do not hesitate to share your thoughts about ADaSci with us.?
Let's work together to make the world of data science even better!?
Cheers!