Analytics Vidhya

JANUARY 8, 2023

Hey, are you the data science geek who spends hours coding, learning a new language, or just exploring new avenues of data science? If all of these describe you, then this Blogathon announcement is for you! Analytics Vidhya is back with its 28th Edition of blogathon, a place where you can share your knowledge about […].

Data Science 328

Data Science Analytics Analytics Hadoop 328

Analytics Vidhya

NOVEMBER 7, 2022

Hello, fellow data science enthusiasts, did you miss imparting your knowledge in the previous blogathon due to a time crunch? Well, it’s okay because we are back with another blogathon where you can share your wisdom on numerous data science topics and connect with the community of fellow enthusiasts.

Data Science 306

Data Science Analytics Analytics Hadoop 306

Data Science Dojo

JULY 3, 2024

Machine Learning : Supervised and unsupervised learning algorithms, including regression, classification, clustering, and deep learning. Tools and frameworks like Scikit-Learn, TensorFlow, and Keras are often covered.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Mlearning.ai

JANUARY 28, 2023

Scikit-Learn: Scikit-Learn is a machine learning library that makes it easy to train and deploy machine learning models. It has a wide range of features, including data preprocessing, feature extraction, deep learning training, and model evaluation. How Do I Use These Libraries?

Machine Learning 52

Machine Learning Machine Learning Data Science ML 52

Pickl AI

JULY 25, 2023

With expertise in programming languages like Python , Java , SQL, and knowledge of big data technologies like Hadoop and Spark, data engineers optimize pipelines for data scientists and analysts to access valuable insights efficiently. Machine Learning: Supervised and unsupervised learning techniques, deep learning, etc.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

NOVEMBER 28, 2024

Without linear algebra, understanding the mechanics of Deep Learning and optimisation would be nearly impossible. Neural Networks These models simulate the structure of the human brain, allowing them to learn complex patterns in large datasets. Neural networks are the foundation of Deep Learning techniques.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

ODSC - Open Data Science

JANUARY 7, 2025

Machine Learning As machine learning is one of the most notable disciplines under data science, most employers are looking to build a team to work on ML fundamentals like algorithms, automation, and so on. Deep Learning Deep learning is a cornerstone of modern AI, and its applications are expanding rapidly.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

Heartbeat

JULY 31, 2023

It automates the process of hyperparameter tuning, making it easy to find the best hyperparameters for a given machine learning problem. This is especially useful for deep learning models, which can have many hyperparameters that need to be optimized. Using Comet saves time and reduces the risk of human error.

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52

Pickl AI

APRIL 2, 2024

Machine Learning: Subset of AI that enables systems to learn from data without being explicitly programmed. Supervised Learning: Learning from labeled data to make predictions or decisions. Unsupervised Learning: Finding patterns or insights from unlabeled data.

Data Science 52

Data Science Machine Learning Machine Learning Predictive Analytics 52

DagsHub

OCTOBER 23, 2024

Popular data lake solutions include Amazon S3 , Azure Data Lake , and Hadoop. Apache Hadoop Apache Hadoop is an open-source framework that supports the distributed processing of large datasets across clusters of computers. Tooling : Apache Tika , ElasticSearch , Databricks , and AWS Glue for metadata extraction and management.

Machine Learning 52

Machine Learning Machine Learning AI AI 52

DagsHub

NOVEMBER 11, 2024

These vector databases store complex data by transforming the original unstructured data into numerical embeddings; this is enabled through deep learning models. AI also plays an important role in this process because it uses deep learning methods to create embeddings that find all the key features of the original data.

AI 52

AI AI Data Lakes Database 52

Pickl AI

JULY 20, 2023

Image Recognition with Deep Learning: Use Python with TensorFlow or PyTorch to build an image recognition model (e.g., When working on these projects, students should focus on understanding the principles of big data analytics, data preprocessing, machine learning, and data visualization using Python libraries. ImageNet).

Analytics 40

Analytics Analytics Big Data Big Data 40