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Bloc.io VS NumPy

Compare Bloc.io VS NumPy and see what are their differences

LibHunt
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives. featured
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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Bloc.io logo Bloc.io

Learn to code and become a web developer in Ruby on Rails, HTML, CSS, Javascript, and jQuery in Bloc's Intense Online Web Development Apprenticeship.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Bloc.io Landing page
    Landing page //
    2023-09-28
  • NumPy Landing page
    Landing page //
    2023-05-13

Bloc.io features and specs

  • Mentorship
    Bloc.io provides one-on-one mentorship with industry professionals, ensuring personalized guidance and support throughout the course.
  • Flexible Learning
    Bloc.io offers flexible scheduling, allowing students to learn at their own pace and accommodate other commitments.
  • Comprehensive Curriculum
    The platform provides a detailed and structured curriculum that covers a wide range of topics in web development, design, and data science.
  • Portfolio Building
    Students have the opportunity to work on real-world projects, helping them build a professional portfolio to showcase to potential employers.
  • Career Services
    Bloc.io offers career support including job search assistance, resume reviews, and interview preparation, aiding students in their job placement efforts.

Possible disadvantages of Bloc.io

  • Cost
    Bloc.io is relatively expensive compared to other online learning platforms, which may not be affordable for everyone.
  • Time Commitment
    Despite its flexible scheduling, the courses require a significant time investment, which may be challenging for those with busy schedules.
  • Pacing
    Some students may find the pacing too fast or too slow, as it depends heavily on self-discipline and motivation.
  • Limited Interaction
    Compared to a traditional classroom setting, there may be limited interaction with peers, which can affect collaborative learning experiences.
  • Variable Quality
    The quality of mentorship can vary depending on the assigned mentor, which may impact the overall learning experience.

NumPy features and specs

  • Performance
    NumPy operations are executed with highly optimized C and Fortran libraries, making them significantly faster than standard Python arithmetic operations, especially for large datasets.
  • Versatility
    NumPy supports a vast range of mathematical, logical, shape manipulation, sorting, selecting, I/O, and basic linear algebra operations, making it a versatile tool for scientific and numeric computing.
  • Ease of Use
    NumPy provides an intuitive, easy-to-understand syntax that extends Python's ability to handle arrays and matrices, lowering the barrier to performing complex scientific computations.
  • Community Support
    With a large and active community, NumPy offers extensive documentation, tutorials, and support for troubleshooting issues, as well as continuous updates and enhancements.
  • Integrations
    NumPy integrates seamlessly with other libraries in Python's scientific stack like SciPy, Matplotlib, and Pandas, facilitating a streamlined workflow for data science and analysis tasks.

Possible disadvantages of NumPy

  • Memory Consumption
    NumPy arrays can consume large amounts of memory, especially when working with very large datasets, which can become a limitation on systems with limited memory capacity.
  • Learning Curve
    For users new to scientific computing or coming from different programming backgrounds, understanding the intricacies of NumPy's operations and efficient usage can take time and effort.
  • Limited GPU Support
    NumPy primarily runs on the CPU and doesn't natively support GPU acceleration, which can be a disadvantage for extremely compute-intensive tasks that could benefit from parallel processing.
  • Dependency on Python
    Since NumPy is a Python library, it depends on the Python runtime environment. This can be a limitation in environments where Python is not the primary language or isn't supported.
  • Indexing Complexity
    Although NumPy's slicing and indexing capabilities are powerful, they can sometimes be complex or unintuitive, especially for multi-dimensional arrays, leading to potential errors and confusion.

Bloc.io videos

+ Add

Bloc.io UX Bootcamp Review Pt 1 | Does it really help get a job after? (2019)

NumPy videos

+ Add

Learn NUMPY in 5 minutes - BEST Python Library!

More videos:

  • Review - Python for Data Analysis by Wes McKinney: Review | Learn python, numpy, pandas and jupyter notebooks
  • Review - Effective Computation in Physics: Review | Learn python, numpy, regular expressions, install python

Category Popularity

0-100% (relative to Bloc.io and NumPy)

Bloc.io

NumPy

Online Learning
100 100%
Online Learning
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Education
100 100%
Education
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Bloc.io and NumPy

Bloc.io Reviews

We have no reviews of Bloc.io yet.
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NumPy Reviews

25 Python Frameworks to Master
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.
Source: kinsta.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.
Source: neptune.ai
Top Python Libraries For Image Processing In 2021
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.
Source: www.analyticsvidhya.com
4 open source alternatives to MATLAB
NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...
Source: opensource.com

Social recommendations and mentions

Based on our record, NumPy seems to be a lot more popular than Bloc.io. While we know about 119 links to NumPy, we've tracked only 1 mention of Bloc.io. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Bloc.io mentions (1)

  • Best Bootcamp
    From an Online bootcamp's perspective: I did bloc.io Online program, which was later swallowed into the Thinkful's part time online program ($9500). Right now, Today, I would rather enroll in Codecademy Pro ($128 / year currently if you are a student) and go through Full Stack Engineer program. I am helping a new coder who's enrolled in this and it's very similar (if not better) to the bloc program I did. I wish I... Source: over 3 years ago

NumPy mentions (119)

  • Building an AI-powered Financial Data Analyzer with NodeJS, Python, SvelteKit, and TailwindCSS - Part 0
    The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / 3 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / 7 months ago
  • Intro to Ray on GKE
    The Python Library components of Ray could be considered analogous to solutions like numpy, scipy, and pandas (which is most analogous to the Ray Data library specifically). As a framework and distributed computing solution, Ray could be used in place of a tool like Apache Spark or Python Dask. It’s also worthwhile to note that Ray Clusters can be used as a distributed computing solution within Kubernetes, as... - Source: dev.to / 8 months ago
  • Streamlit 101: The fundamentals of a Python data app
    It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”. - Source: dev.to / 9 months ago
  • A simple way to extract all detected objects from image and save them as separate images using YOLOv8.2 and OpenCV
    The OpenCV image is a regular NumPy array. You can see it shape:. - Source: dev.to / 9 months ago
View more

What are some alternatives?

When comparing Bloc.io and NumPy, you can also consider the following products

Codeplace - Learn how to code by building real web apps

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

PurelyFunctional.tv - Online Clojure training courses with a subscription model.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

GoSkills - GoSkills offers bite-sized business courses.

OpenCV - OpenCV is the world's biggest computer vision library

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