English | Size: 6.90 GB
Genre: eLearning
What you’ll learn
Python
Python instructors on Udemy specialize in everything from software development to data analysis, and are known for their effective, friendly instruction for students of all levels.
Fundamental stuff of Python and its library Numpy
What is the AI, Machine Learning and Deep Learning
History of Machine Learning
Turing Machine and Turing Test
The Logic of Machine Learning such as Machine Learning models and algorithms, Gathering data, Data pre-processing, Training and testing the model etc.
What is Artificial Neural Network (ANN)
Anatomy of NN
Tensor Operations
Python instructors on Udemy specialize in everything from software development to data analysis, and are known for their effective, friendly instruction for students of all levels.
Machine learning isn’t just useful for predictive texting or smartphone voice recognition. Machine learning is constantly being applied to new industries and new problems. Whether you’re a marketer, video game designer, or programmer, I am here to help you apply machine learning to your work.
The Engine of NN
Keras
Tensorflow
Convolutional Neural Network
Recurrent Neural Network and LTSM
Transfer Learning
Machine Learning
Deep Learning
Machine Learning with Python
Python Programming
Deep Learning with Python
If you have some programming experience, Python might be the language for you
Learn Fundamentals of Python for effectively using Data Science
Data Manipulation
Learn how to handle with big data
Learn how to manipulate the data
Learn how to produce meaningful outcomes
Learn Fundamentals of Python for effectively using Data Science
Numpy arrays
Series and Features
Combining Dataframes, Data Munging and how to deal with Missing Data
How to use Matplotlib library and start to journey in Data Visualization
Also, why you should learn Python and Pandas Library
Learn Data Science with Python
Examine and manage data structures
Handle wide variety of data science challenges
Select columns and filter rows
Arrange the order and create new variables
Create, subset, convert or change any element within a vector or data frame
Transform and manipulate an existing and real data
The Logic of Matplotlib
What is Matplotlib
Using Matplotlib
Pyplot – Pylab – Matplotlib
Figure, Subplot, Multiplot, Axes,
Figure Customization
Data Visualization
Plot Customization
Grid, Spines, Ticks
Basic Plots in Matplotlib
Seaborn library with these topics
What is Seaborn
Controlling Figure Aesthetics
Color Palettes
Basic Plots in Seaborn
Multi-Plots in Seaborn
Regression Plots and Squarify
Geoplotlib with these topics
What is Geoplotlib
Tile Providers and Custom Layers
R and Python in the same course. You decide which one you would go for!
R was built as a statistical language, it suits much better to do statistical learning and R is a statistical programming software favoured by many academia
Since R was built as a statistical language, it suits much better to do statistical learning. It represents the way statisticians think pretty well, so anyone with a formal statistics background can use R easily. Python, on the other hand, is a better choice for machine learning with its flexibility for production use, especially when the data analysis tasks need to be integrated with web applications. If you enroll this course you will have a chance to learn both
You will learn R and Python from scratch
Because data can mean an endless number of things, it’s important to choose the right visualization tools for the job.
you’re interested in learning Tableau, D3 js, After Effects, or Python, has a course for you.
Learn how to use NumPy, Pandas, Seaborn , Matplotlib , Machine Learning, and more!
Who this course is for:
Anyone interested in data sciences
Anyone who plans a career in data scientist,
Software developer whom want to learn data science,
Anyone eager to learn Data Science with no coding background
Statisticians, academic researchers, economists, analysts and business people
Professionals working in analytics or related fields
Anyone who is particularly interested in big data, machine learning and data intelligence
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