Python (ML and AI)
Machine learning and AI using Python involve using Python libraries such as scikit-learn and TensorFlow to create algorithms that can make predictions.
Python ML and AI
Master the exciting domains of Python Machine Learning and Artificial Intelligence with Tech Cryptor’s (ML and AI) course for professionals and enthusiasts in Mumbai, India.
This Tech Cryptors Python ML and AI program offers a deep dive into data analysis, predictive modeling, and intelligent algorithms using Python. Explore popular libraries like TensorFlow and scikit-learn to create and deploy robust machine learning models. Gain practical insights into artificial intelligence fundamentals and learn how to apply them to solve real-world challenges. With expert guidance, hands-on exercises, and industry-relevant projects, this course empowers you to thrive in the dynamic field of ML and AI using Python.
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Overview about the Python, applicaitons of python
Installation of PyCharm software and overview of its file structure
Learn about the syntax, indentation and comments in Python
Learn differnt methods to declare and define variables along with its naming rules
Learn about differnt data types and data structures in python
Lear about type casting which helps to convert any data type into another
Learn & code about Arithmetic, Relational, Logical, Assignment, etc. Operators used in Python
Create & understand different types decision making, loops and its statements
Learn about if-else statement to execute a block of code among conditional alternatives
Learn about nested if-else to execute the block of code inside other if-else statements
Learn about while loop which can execute a set of statements as long as a condition is true
Learn about for loop to iterate over the members of a sequence in order, executing the block each time
Learn about nested loop where inner loop will be executed one time for each iteration of the outer loop
Performing & understanding strings etc. practically.
Learn to take inputs from the user in differnt data types
Learn different types of data structures into python
Learn different list functionalities to handle list flawlessly
Learn tuple to store multiple items in a single variable
Learn dictionary collection to store data values in key:value pairs
Learn about functions and lambda functions in python
Learn about differnt function argumants to maipulate function as our requirements
Learn about exception in python to create error free codes
Learn to use regular expression into python for matching text patterns
Understand and perform python modules efficienty
Learn about Math module to handle different math function very easily
Learn to handle os module to manipulate operating system functionality efficiently
Learn to create classes and methods in python create object oriented codes
Learn inheritance to define a class that inherits all the methods and properties from another class
Learn to create abstract class to hide unnecessary information from the user
Learn about data encapsulation to wrap data and the methods that work on data within one unit
Learn polymorphism which define methods in the child class that have the same name as the methods in the parent class
Learn file handling which allows you to perform a wide range of operations, such as creating, reading, writing, appending, renaming, etc.
Introduction and overview about machine learning
Explanation about different types of machine learning with different application and algorithm examples
Introduction to different machine learning terminologies
Learn about simple linear regression for modelling the relationship between a scalar response and one or more explanatory variables
Learn about multi-linear regression for predicting the value of one dependent variable based on two or more independent variables
Learn logistic regression which predicts the output of a categorical dependent variable
Learn polynomial regression that models the relationship between a dependent and independent variable as nth degree polynomial
Learn decision tree classification which makes predictions based on how a previous set of questions were answered
Learn about random forest classification algorithm which consisting of many decisions trees
Learn about support vector machine classification to create the best line or decision boundary that can segregate n-dimensional space into classes
Learn about K-nearest neighbour algorithm which stores all the available data and classifies a new data point based on the similarity
Learn bagging algorithm which reduces variance within a noisy dataset
Coding for different Regression algorithms in Python.
Coding for different Classification algorithms in Python.
Performing digit recognizer practically on your laptop.
Coding for making your own CHAT BOT.
Learning different regression algorithms using python.
Practically performing them to get output by understanding logic.
Learning & Understanding concept behind NEURAL NETWORKS.
Practically coding for neural network.
Understanding logic behind Convolutional Neural Network.
Making your own project for Converting Images into Texts
Understanding basic logic behind Graphical User Interface using Python.
Making your own project for Converting Images into Texts.
Coding for making TIC-TAC-TOE as AUTO PLAYER game.
Coding for controlling system using voice commands.
Coding for performing different operations using voice commands.
Making your own JARVIS (Chat assistant), which will listen to your commands for opening Facebook, YouTube & performing arious Operations.
Click Here to view a complete step-by-step guide on how to install Python
Click Here to view a complete step-by-step guide on how to install PyCharmÂ
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