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Python Course for Machine learning in Kolkata

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Python is a versatile language that you can use for building all sorts of applications, including machine learning models. In Kolkata, there are many institutes that offer training in Python for machine learning. We provide professional Python course for Machine learning in Kolkata with projects.
These institutes provide comprehensive training that covers all the important aspects of machine learning using Python. The trainers at these institutes are experienced professionals who have in-depth knowledge of both Python and machine learning.
Thus, if you are looking to get started with machine learning in Kolkata, enrolling in a course at one of these institutes would be a good idea.


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    Python for Data Science Course Syllabus

    • Welcome to Machine Learning. Here are a few resources to get you started!
    • Welcome to the Machine Learning Section!
    • Supervised Learning Overview
    • Evaluating Performance - Classification Error Metrics
    • Evaluating Performance - Regression Error Metrics
    • Machine Learning with Python

    • Linear Regression Theory
    • model_selection Updates for SciKit Learn 0.18
    • Linear Regression with Python - Part 1
    • Linear Regression with Python - Part 2
    • Linear Regression Project Overview
    • Linear Regression Project Solution

    • Bias Variance Trade-Off

    • Logistic Regression Theory
    • Logistic Regression with Python - Part 1
    • Logistic Regression with Python - Part 2
    • Logistic Regression with Python - Part 3
    • Logistic Regression Project Overview
    • Logistic Regression Project Solutions

    • KNN Theory
    • KNN with Python
    • KNN Project Overview
    • KNN Project Solutions

    • Introduction to Tree Methods
    • Decision Trees and Random Forest with Python
    • Decision Trees and Random Forest Project Overview
    • Decision Trees and Random Forest Solutions Part 1
    • Decision Trees and Random Forest Solutions Part 2

    • SVM Theory
    • Support Vector Machines with Python
    • SVM Project Overview
    • SVM Project Solutions

    • K Means Algorithm Theory
    • K Means Project Overview
    • K Means Project Overview
    • K Means Project Solutions

    • Principal Component Analysis
    • PCA with Python

    • Recommender Systems
    • Recommender Systems with Python - Part 1
    • Recommender Systems with Python - Part 2

    • Natural Language Processing Theory
    • NLP with Python - Part 1
    • NLP with Python - Part 2
    • NLP with Python - Part 3
    • NLP Project Overview
    • NLP Project Solutions

    • Welcome to the Deep Learning Section!
    • Introduction to Artificial Neural Networks (ANN)
    • Perceptron Model
    • Neural Networks
    • Activation Functions
    • Multi-Class Classification Considerations
    • Cost Functions and Gradient Descent
    • Backpropagation
    • TensorFlow vs Keras
    • TF Syntax Basics - Part One - Preparing the Data
    • TF Syntax Basics - Part Two - Creating and Training the Model
    • TF Syntax Basics - Part Three - Model Evaluation
    • TF Regression Code Along - Exploratory Data Analysis
    • TF Regression Code Along - Exploratory Data Analysis - Continued
    • TF Regression Code Along - Data Preprocessing and Creating a Model
    • TF Regression Code Along - Model Evaluation and Predictions
    • TF Classification Code Along - EDA and Preprocessing
    • TF Classification - Dealing with Overfitting and Evaluation
    • TensorFlow 2.0 Project Options Overview
    • TensorFlow 2.0 Project Notebook Overview
    • Keras Project Solutions - Dealing with Missing Data
    • Keras Project Solutions - Dealing with Missing Data - Part Two
    • Keras Project Solutions - Categorical Data
    • Keras Project Solutions - Data PreProcessing
    • Keras Project Solutions - Data PreProcessing
    • Keras Project Solutions - Creating and Training a Model
    • Keras Project Solutions - Model Evaluation
    • Tensorboard

    • Welcome to the Big Data Section!
    • Big Data Overview
    • Spark Overview
    • AWS Account Set-Up
    • EC2 Instance Set-Up
    • SSH with Mac or Linux
    • PySpark Setup
    • Lambda Expressions Review
    • Introduction to Spark and Python
    • RDD Transformations and Actions

    • ---blank----

    Why learn Python course for Machine Learning?

    The main reasons why Python is used for machine learning are:

    Python is Flexible: In terms of flexibility, Python is ideal for developers who wish to script applications and websites. This is because Python is a simple language that does not require as much coding skill as other languages.

    Easy to Learn: The main goal of Python is to keep things simple and readable, making it an excellent tool for beginners. Furthermore, Python has a relatively low learning curve, giving programmers more freedom to experiment. As compared to the old languages, Python has fewer lines of code, so programmers can play around more.

    Python is Open Source: Essentially, Python is free and designed to run on Windows and Linux environments. It can also be ported to other platforms as well.

    Large community: Python is widely used in academia and industry. This means there are many analytics libraries available. Additionally, Python users have access to Stack Overflow, mailing lists, and user-contributed code and documentation. Python is becoming more and more popular every day.

    Certificate From Acesoftech Academy

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    Start attending interviews from 2nd month of the course itself

    250+ Hiring Partner companies
    Dedicated Mentors for Doubts sessions
    Good Lab space for Practice everyday after class
    Only one batch per month with 15 students
    100% job guaranteed program
    Certified & 5+ years Experienced Trainers
    Dedicated HR Teams in all Major cities in India

    Tools You Will Master

    Advantages of Training at Acesoftech Academy

    Flexible Online Live and Classroom Training

    100% Internship/Job Guarantee Programs

    Dedicated Placements Team

    Mastery-Level Certifications that are Globally Accepted

    Backup Classes & Lifetime LMS Access

    Completely Practical Oriented Approach

    Hands-on training on the capstone projects

    Free Technical Support & Individual Career Counselling

    Expert mentoring Weekly Tests & Assignments

    Mock-up Exams, and Interviews

    Meet-ups, Workshops, Hackathons & Conferences

    Exclusive programs for Non-IT professionals

    FAQs

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    This is the third item's accordion body. It is hidden by default, until the collapse plugin adds the appropriate classes that we use to style each element. These classes control the overall appearance, as well as the showing and hiding via CSS transitions. You can modify any of this with custom CSS or overriding our default variables. It's also worth noting that just about any HTML can go within the .accordion-body, though the transition does limit overflow.

    Why learn Python Course for Data Science?

    If you're looking to get ahead in the tech world, learning Java is a great way to do it. Not only is Java a popular and versatile programming language, but it's also relatively easy to learn. And once you've learned Java, you'll be able to apply your skills to a wide range of different tasks and projects.


    Here are just a few of the reasons why learning Java can be beneficial for your career:

    1. Java is one of the most popular programming languages in the world. That means that there are plenty of opportunities out there for Java developers. And because Java is so versatile, you'll be able to use your skills on a variety of different projects.


    2. Learning Java will give you a solid foundation in programming principles. Once you've learned the basics of Java, you'll be able to pick up other languages more easily. That's because understanding the principles of programming is more important than knowing the specifics of any one language.


    3. Java is used in a wide range of industries, from web development to software engineering. That means that if you want to change careers or move into a new field, learning Java will give you the transferable skills you need.


    4. Overall, learning Java can be extremely beneficial for your career prospects. So if you're looking to get ahead in the tech world, make sure you add Java to your list of skills!

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