Data Science Essentials Advanced Algorithms and Visualizations
Data Science Essentials Advanced Algorithms and Visualizations
MP4 | Video: AVC 1920x1080 | Audio: AAC, 48 KHz @ 121 Kbps 2ch
Duration: 1 hrs 50 mins | Language: English | 389 MB
Genre: eLearning Video
MP4 | Video: AVC 1920x1080 | Audio: AAC, 48 KHz @ 121 Kbps 2ch
Duration: 1 hrs 50 mins | Language: English | 389 MB
Genre: eLearning Video
This course will make you look beyond the fundamentals with beautiful data visualizations with Seaborn and ggplot, web development with Bottle, and even the new frontiers of deep learning with Theano and TensorFlow. We start with SVM and random forest for classification and regression. We look at big data, deep learning, and language processing. Then we use graph analysis techniques for very interesting and trending social media analytics. Finally, we take a complete overview of the principal machine learning algorithms, graph analysis techniques, and all the visualization and deployment tools that make it easier to present your results to an audience of both data science experts and business users.
Delve deeper into machine learning with Pyton
All the code and supporting files for this course are available on Github at https://github.com/PacktPublishing/Data-Science-Essentials-Advanced-Algorithms-and-Visualizations
Style and Approach
The course is structured as a data science project. You will always benefit from clear code and simplified examples to help you understand the underlying mechanics and real-world datasets.
What You Will Learn
- Set up an experimental pipeline to test your data science hypotheses
- Choose the most effective and scalable learning algorithm for your data science tasks
- Optimize your machine learning models to get the best performance
- Explore and cluster graphs, taking advantage of interconnections and links in your data
ADVANCED MACHINE LEARNING
SOCIAL NETWORK ANALYSIS
VISUALIZATION, INSIGHTS, AND RESULTS
- The Course Overview
- Support Vector Machine
- Ensemble Strategies
- Dealing with Big Data
- Approaching Deep Learning
- A Peek at Natural Language Processing (NLP)
SOCIAL NETWORK ANALYSIS
- Introduction to Graph Theory
- Graph Algorithms
- Graph Loading, Dumping, and Sampling
VISUALIZATION, INSIGHTS, AND RESULTS
- ntroducing the Basics of Matplotlib
- Wrapping Up Matplotlib's Commands
- Interactive Visualizations with Bokeh
- Advanced Data-learning Representations
Data Science Essentials Advanced Algorithms and Visualizations
Data Science Essentials Advanced Algorithms and Visualizations
