Projects with this topic
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As the first project for Talentsprint's Techwise, our group of five aims to create a functional and unique rendition of the classic chess game. The project begins on July 6 and is presented on August 22.
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Machine Learning Basics - implementation of: loss functions (cross entropy loss, L1 loss, L2 loss, hinge loss), regularizations (L1 regularizer, L2 regularizer, early stopping), gradient check, optimizers, training a simple deep model.
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"Cloud container data analytics, statistical modeling, and machine learning on distributed databases". "A free opensource alternative to SPSS, SAS, MATLAB, PowerBI, Tableau and Alteryx". Runs on Linux, Windows, MacOS, and in the cloud via containers.
LaTeX statistics sas spss matlab Python R spark cloud gcp Oracle azure Amazon Web S... Kubernetes containers Docker ML machine lear... regression clustering TiDB Yugabyte MySQL MariaDB SQL sparkr pyspark RStudio - KNIME Anal... Apache Spark... PyTorch MXNet Chainer keras gluon Scikit-learn... ONNX MLOps - Anac... NumPy Ipython) StatsModels pytest dask Koalas API -... Tornado - Py... Altair Bokeh Jupyter Voila Plotly/Dash matplotlib Seaborn - C#... SASPy - R: T... ggplot2 shiny dash Sparklyr BlueSky Stat... Jamovi - Int... vs code Vim - Tableau TabPy Tableau Buil... Python) - PL... SQL Developer PostgreSQL MySQL/MariaDB pgAdmin4 dbeaver MySQL Workbench Spark SQL Delta Lake Angular 2+ React .NET Core JavaScript (JS) Typescript (TS) Blazor Razor html5 CSS3 AWS EC2 Servers docker-compose podman Red Hat Ente... Oracle Linux fedora centos Ubuntu (WSL 2) debian Kestrel nginx Apache web s... jira Git Gitlab CI/CD... Code Climate... Ansible helm Terraform Cloudera Dat... nifi blender godot MS OfficeUpdated -
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Terminal application with python 3. Fetches records from chat site with selenium webdriver. Saves records from chat site in human-readable and script-usable format, compiles statistics from chat conversations, and serves me with invoices.
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Course called Introduction to Scientific Python. Please see the syllabus.
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This is a Collaborative-Based Product Recommendation Engine which recommends most correlated products to the Customer based on the Ratings patterns of other customers who bought that same product also.
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This is where the lessons and challenges for the python crash course will be posted.
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