1. Flutter - Build Apps on both iOS and Android

Firebase -

2. Flask - Build website with Python

3. SQL or NoSQL



“For beginners, starting out with Python–and especially Python 3–is a great way to learn programming quickly. It’s a diverse and intuitive language and tons of awesome companies like Google, NASA, Facebook, and Spotify are using it!”
— https://learntocodewith.me/programming/python/python-2-vs-python-3/#history-of-python2-vs-3
“1. You can use apps such as Pythonista 3 to install python on your iPad
2. or web-based IDEs like IPython Notebook.”
— https://www.quora.com/Can-you-do-Python-coding-on-an-iPad

colab.research.google.com

“https://colab.research.google.com/notebooks/intro.ipynb#recent=true”
“https://notebooks.azure.com/”

EDX: INTRODUCTION TO COMPUTER SCIENCE AND PROGRAMMING USING PYTHON

What the course covers: Python syntax, simple algorithms, how to think computationally, data structures, and more

Course URL: https://learntocodewith.me/introduction-to-python

  • Instructed by: John Guttag, Eric Grimson, and Ana Bell

  • Price: Free

UDEMY: THE COMPLETE PYTHON 3 COURSE

What the course covers: All the basics like strings, expressions, loops, functions, exception handling, etc. Great way for someone with zero prior knowledge to learn to code Python.

COURSERA: PROGRAMMING FOR EVERYBODY (GETTING STARTED WITH PYTHON)

What the course covers: Covers core programming tools such as functions and loops, as well as variables to store, retrieve, and calculate information.

There are several Machine Learning Software that is available in the market. Enlisted below are the most popular ones among them.

1. Scikit-learn is for machine learning development in python. It provides a library for the Python programming language.

Features:

  • It helps in data mining and data analysis.

  • It provides models and algorithms for Classification, Regression, Clustering, Dimensional reduction, Model selection, and Pre-processing.

Official Website: scikit-learn

2. PyTorch is a Torch based, Python machine learning library. The torch is a Lua based computing framework, scripting language, and machine learning library.

Features:

  • It helps in building neural networks through Autograd Module.

  • It provides a variety of optimization algorithms for building neural networks.

  • PyTorch can be used on cloud platforms.

  • It provides distributed training, various tools, and libraries.

Official Website: Pytorch

3. TensorFlow provides a JavaScript library which helps in machine learning. APIs will help you to build and train the models.

Features:

  • Helps in training and building your models.

  • You can run your existing models with the help of TensorFlow.js which is a model converter.

  • It helps in the neural network.

Official Website: Tensorflow

4. Google Colab is a cloud service which supports Python. It will help you in building the machine learning applications using the libraries of PyTorch, Keras, TensorFlow, and OpenCV

Features:

  • It helps in machine learning education.

  • Assists in machine learning research.

Official Website: Colab

5. Keras is an API for neural networks. It helps in doing quick research and is written in Python.

Features:

  • It can be used for easy and fast prototyping.

  • It supports convolution networks.

  • It assists recurrent networks.

  • It supports a combination of two networks.

  • It can be run on the CPU and GPU.

Official Website: Keras

6. Rapid Miner provides a platform for machine learning, deep learning, data preparation, text mining, and predictive analytics. It can be used for research, education and application development.

Features:

  • Through GUI, it helps in designing and implementing analytical workflows.

  • It helps with data preparation.

  • Result Visualization.

  • Model validation and optimization.

Pros:

  • Extensible through plugins.

  • Easy to use.

  • No programming skills are required.

It has four plans:

  • Free plan

  • Small: $2500 per year.

  • Medium: $5000 per year.

  • Large: $10000 per year.

Official Website: Rapid Miner

1. Knime

Knime is an open-source machine learning tool that is based on GUI. The best thing about Knime is, it doesn’t require any knowledge of programming. One can still avail of the facilities provided by Knime. It is generally used for data relevant purposes. For example, data manipulation, data mining, etc. Moreover, it processes data by creating different various workflows and then execute them. It comes with repositories that are full of different nodes. These nodes are then brought into the Knime portal. And finally, a workflow of nodes is created and executed.

2. Google Cloud AutoML

The objective of Google cloud AutoML is to make artificial intelligence accessible to everyone. What Google Cloud AutoML does is, it provides the models which are pre-trained to the users in order to create various services. For example, text recognition, speech recognition, etc.

3. Jupyter Notebook

Jupyter notebook is one of the most widely used machine learning tools among all. It is a very fast processing as well as an efficient platform. Moreover, it supports three languages viz. Julia, R, Python.

4. Azure machine learning studio

Azure machine learning studio is launched by Microsoft. Just like, Google’s Cloud AutoML, this is Microsoft’s product which provides machine learning services to the users. Azure machine learning studio is a very easy way to form connections of modules and datasets.

5. IBM Watson

IBM Watson is a web interface that is given by IBM for using Watson. Watson is a human interaction Q and A system which is based on Natural Language processing. Watson is applied in various fields such as automated learning, information extraction, etc.

6. Amazon Machine Learning

It should come as no surprise that Amazon offers an impressive number of machine learning tools. According to the AWS website, Amazon Machine Learning is a managed service for building Machine Learning models and generating predictions. Amazon Machine Learning includes an automatic data transformation tool, simplifying the machine learning tool even further for the user. In addition, Amazon also offers other machine learning tools such as Amazon SageMaker, which is a fully-managed platform that makes it easy for developers and data scientists to utilize machine learning models.