More on Web3 & Crypto
Dylan Smyth
4 years ago
10 Ways to Make Money Online in 2022
As a tech-savvy person (and software engineer) or just a casual technology user, I'm sure you've had this same question countless times: How do I make money online? and how do I make money with my PC/Mac?
You're in luck! Today, I will list the top 5 easiest ways to make money online. Maybe a top ten in the future? Top 5 tips for 2022.
1. Using the gig economy
There are many websites on the internet that allow you to earn extra money using skills and equipment that you already own.
I'm referring to the gig economy. It's a great way to earn a steady passive income from the comfort of your own home. For some sites, premium subscriptions are available to increase sales and access features like bidding on more proposals.
Some of these are:
- Freelancer
- Upwork
- Fiverr (⭐ my personal favorite)
- TaskRabbit
2. Mineprize
MINEPRIZE is a great way to make money online. What's more, You need not do anything! You earn money by lending your idle CPU power to MINEPRIZE.
To register with MINEPRIZE, all you need is an email address and a password. Let MINEPRIZE use your resources, and watch the money roll in! You can earn up to $100 per month by letting your computer calculate. That's insane.
3. Writing
“O Romeo, Romeo, why art thou Romeo?” Okay, I admit that not all writing is Shakespearean. To be a copywriter, you'll need to be fluent in English. Thankfully, we don't have to use typewriters anymore.
Writing is a skill that can earn you a lot of money (claps for the rhyme).
Here are a few ways you can make money typing on your fancy keyboard:
Self-publish a book
Write scripts for video creators
Write for social media
Book-checking
Content marketing help
What a list within a list!
4. Coding
Yes, kids. You've probably coded before if you understand
You've probably coded before if you understand
print("hello world");
Computational thinking (or coding) is one of the most lucrative ways to earn extra money, or even as a main source of income.
Of course, there are hardcode coders (like me) who write everything line by line, binary di — okay, that last part is a bit exaggerated.
But you can also make money by writing websites or apps or creating low code or no code platforms.
But you can also make money by writing websites or apps or creating low code or no code platforms.
Some low-code platforms
Sheet : spreadsheets to apps :
Loading... We'll install your new app... No-Code Your team can create apps and automate tasks. Agile…
www.appsheet.com
Low-code platform | Business app creator - Zoho Creator
Work is going digital, and businesses of all sizes must adapt quickly. Zoho Creator is a...
www.zoho.com
Sell your data with TrueSource. NO CODE NEEDED
Upload data, configure your product, and earn in minutes.
www.truesource.io
Cool, huh?
5. Created Content
If we use the internet correctly, we can gain unfathomable wealth and extra money. But this one is a bit more difficult. Unlike some of the other items on this list, it takes a lot of time up front.
I'm referring to sites like YouTube and Medium. It's a great way to earn money both passively and actively. With the likes of Jake- and Logan Paul, PewDiePie (a.k.a. Felix Kjellberg) and others, it's never too late to become a millionaire on YouTube. YouTubers are always rising to the top with great content.
6. NFTs and Cryptocurrency
It is now possible to amass large sums of money by buying and selling digital assets on NFTs and cryptocurrency exchanges. Binance's Initial Game Offer rewards early investors who produce the best results.
One awesome game sold a piece of its plot for US$7.2 million! It's Axie Infinity. It's free and available on Google Play and Apple Store.
7. Affiliate Marketing
Affiliate marketing is a form of advertising where businesses pay others (like bloggers) to promote their goods and services. Here's an example. I write a blog (like this one) and post an affiliate link to an item I recommend buying — say, a camera — and if you buy the camera, I get a commission!
These programs pay well:
- Elementor
- AWeber
- Sendinblue
- ConvertKit\sLeadpages
- GetResponse
- SEMRush\sFiverr
- Pabbly
8. Start a blog
Now, if you're a writer or just really passionate about something or a niche, blogging could potentially monetize that passion!
Create a blog about anything you can think of. It's okay to start right here on Medium, as I did.
9. Dropshipping
And I mean that in the best possible way — drop shopping is ridiculously easy to set up, but difficult to maintain for some.
Luckily, Shopify has made setting up an online store a breeze. Drop-shipping from Alibaba and DHGate is quite common. You've got a winner if you can find a local distributor willing to let you drop ship their product!
10. Set up an Online Course
If you have a skill and can articulate it, online education is for you.
Skillshare, Pluralsight, and Coursera have all made inroads in recent years, upskilling people with courses that YOU can create and earn from.
That's it for today! Please share if you liked this post. If not, well —
Juxtathinka
3 years ago
Why Is Blockchain So Popular?
What is Bitcoin?
The blockchain is a shared, immutable ledger that helps businesses record transactions and track assets. The blockchain can track tangible assets like cars, houses, and land. Tangible assets like intellectual property can also be tracked on the blockchain.
Imagine a blockchain as a distributed database split among computer nodes. A blockchain stores data in blocks. When a block is full, it is closed and linked to the next. As a result, all subsequent information is compiled into a new block that will be added to the chain once it is filled.
The blockchain is designed so that adding a transaction requires consensus. That means a majority of network nodes must approve a transaction. No single authority can control transactions on the blockchain. The network nodes use cryptographic keys and passwords to validate each other's transactions.
Blockchain History
The blockchain was not as popular in 1991 when Stuart Haber and W. Scott Stornetta worked on it. The blocks were designed to prevent tampering with document timestamps. Stuart Haber and W. Scott Stornetta improved their work in 1992 by using Merkle trees to increase efficiency and collect more documents on a single block.
In 2004, he developed Reusable Proof of Work. This system allows users to verify token transfers in real time. Satoshi Nakamoto invented distributed blockchains in 2008. He improved the blockchain design so that new blocks could be added to the chain without being signed by trusted parties.
Satoshi Nakomoto mined the first Bitcoin block in 2009, earning 50 Bitcoins. Then, in 2013, Vitalik Buterin stated that Bitcoin needed a scripting language for building decentralized applications. He then created Ethereum, a new blockchain-based platform for decentralized apps. Since the Ethereum launch in 2015, different blockchain platforms have been launched: from Hyperledger by Linux Foundation, EOS.IO by block.one, IOTA, NEO and Monero dash blockchain. The block chain industry is still growing, and so are the businesses built on them.
Blockchain Components
The Blockchain is made up of many parts:
1. Node: The node is split into two parts: full and partial. The full node has the authority to validate, accept, or reject any transaction. Partial nodes or lightweight nodes only keep the transaction's hash value. It doesn't keep a full copy of the blockchain, so it has limited storage and processing power.
2. Ledger: A public database of information. A ledger can be public, decentralized, or distributed. Anyone on the blockchain can access the public ledger and add data to it. It allows each node to participate in every transaction. The distributed ledger copies the database to all nodes. A group of nodes can verify transactions or add data blocks to the blockchain.
3. Wallet: A blockchain wallet allows users to send, receive, store, and exchange digital assets, as well as monitor and manage their value. Wallets come in two flavors: hardware and software. Online or offline wallets exist. Online or hot wallets are used when online. Without an internet connection, offline wallets like paper and hardware wallets can store private keys and sign transactions. Wallets generally secure transactions with a private key and wallet address.
4. Nonce: A nonce is a short term for a "number used once''. It describes a unique random number. Nonces are frequently generated to modify cryptographic results. A nonce is a number that changes over time and is used to prevent value reuse. To prevent document reproduction, it can be a timestamp. A cryptographic hash function can also use it to vary input. Nonces can be used for authentication, hashing, or even electronic signatures.
5. Hash: A hash is a mathematical function that converts inputs of arbitrary length to outputs of fixed length. That is, regardless of file size, the hash will remain unique. A hash cannot generate input from hashed output, but it can identify a file. Hashes can be used to verify message integrity and authenticate data. Cryptographic hash functions add security to standard hash functions, making it difficult to decipher message contents or track senders.
Blockchain: Pros and Cons
The blockchain provides a trustworthy, secure, and trackable platform for business transactions quickly and affordably. The blockchain reduces paperwork, documentation errors, and the need for third parties to verify transactions.
Blockchain security relies on a system of unaltered transaction records with end-to-end encryption, reducing fraud and unauthorized activity. The blockchain also helps verify the authenticity of items like farm food, medicines, and even employee certification. The ability to control data gives users a level of privacy that no other platform can match.
In the case of Bitcoin, the blockchain can only handle seven transactions per second. Unlike Hyperledger and Visa, which can handle ten thousand transactions per second. Also, each participant node must verify and approve transactions, slowing down exchanges and limiting scalability.
The blockchain requires a lot of energy to run. In addition, the blockchain is not a hugely distributable system and it is destructible. The security of the block chain can be compromised by hackers; it is not completely foolproof. Also, since blockchain entries are immutable, data cannot be removed. The blockchain's high energy consumption and limited scalability reduce its efficiency.
Why Is Blockchain So Popular?
The blockchain is a technology giant. In 2018, 90% of US and European banks began exploring blockchain's potential. In 2021, 24% of companies are expected to invest $5 million to $10 million in blockchain. By the end of 2024, it is expected that corporations will spend $20 billion annually on blockchain technical services.
Blockchain is used in cryptocurrency, medical records storage, identity verification, election voting, security, agriculture, business, and many other fields. The blockchain offers a more secure, decentralized, and less corrupt system of making global payments, which cryptocurrency enthusiasts love. Users who want to save time and energy prefer it because it is faster and less bureaucratic than banking and healthcare systems.
Most organizations have jumped on the blockchain bandwagon, and for good reason: the blockchain industry has never had more potential. The launch of IBM's Blockchain Wire, Paystack, Aza Finance and Bloom are visible proof of the wonders that the blockchain has done. The blockchain's cryptocurrency segment may not be as popular in the future as the blockchain's other segments, as evidenced by the various industries where it is used. The blockchain is here to stay, and it will be discussed for a long time, not just in tech, but in many industries.
Read original post here
Coinbase
4 years ago
10 Predictions for Web3 and the Cryptoeconomy for 2022
By Surojit Chatterjee, Chief Product Officer
2021 proved to be a breakout year for crypto with BTC price gaining almost 70% yoy, Defi hitting $150B in value locked, and NFTs emerging as a new category. Here’s my view through the crystal ball into 2022 and what it holds for our industry:
1. Eth scalability will improve, but newer L1 chains will see substantial growth — As we welcome the next hundred million users to crypto and Web3, scalability challenges for Eth are likely to grow. I am optimistic about improvements in Eth scalability with the emergence of Eth2 and many L2 rollups. Traction of Solana, Avalanche and other L1 chains shows that we’ll live in a multi-chain world in the future. We’re also going to see newer L1 chains emerge that focus on specific use cases such as gaming or social media.
2. There will be significant usability improvements in L1-L2 bridges — As more L1 networks gain traction and L2s become bigger, our industry will desperately seek improvements in speed and usability of cross-L1 and L1-L2 bridges. We’re likely to see interesting developments in usability of bridges in the coming year.
3. Zero knowledge proof technology will get increased traction — 2021 saw protocols like ZkSync and Starknet beginning to get traction. As L1 chains get clogged with increased usage, ZK-rollup technology will attract both investor and user attention. We’ll see new privacy-centric use cases emerge, including privacy-safe applications, and gaming models that have privacy built into the core. This may also bring in more regulator attention to crypto as KYC/AML could be a real challenge in privacy centric networks.
4. Regulated Defi and emergence of on-chain KYC attestation — Many Defi protocols will embrace regulation and will create separate KYC user pools. Decentralized identity and on-chain KYC attestation services will play key roles in connecting users’ real identity with Defi wallet endpoints. We’ll see more acceptance of ENS type addresses, and new systems from cross chain name resolution will emerge.
5. Institutions will play a much bigger role in Defi participation — Institutions are increasingly interested in participating in Defi. For starters, institutions are attracted to higher than average interest-based returns compared to traditional financial products. Also, cost reduction in providing financial services using Defi opens up interesting opportunities for institutions. However, they are still hesitant to participate in Defi. Institutions want to confirm that they are only transacting with known counterparties that have completed a KYC process. Growth of regulated Defi and on-chain KYC attestation will help institutions gain confidence in Defi.
6. Defi insurance will emerge — As Defi proliferates, it also becomes the target of security hacks. According to London-based firm Elliptic, total value lost by Defi exploits in 2021 totaled over $10B. To protect users from hacks, viable insurance protocols guaranteeing users’ funds against security breaches will emerge in 2022.
7. NFT Based Communities will give material competition to Web 2.0 social networks — NFTs will continue to expand in how they are perceived. We’ll see creator tokens or fan tokens take more of a first class seat. NFTs will become the next evolution of users’ digital identity and passport to the metaverse. Users will come together in small and diverse communities based on types of NFTs they own. User created metaverses will be the future of social networks and will start threatening the advertising driven centralized versions of social networks of today.
8. Brands will start actively participating in the metaverse and NFTs — Many brands are realizing that NFTs are great vehicles for brand marketing and establishing brand loyalty. Coca-Cola, Campbell’s, Dolce & Gabbana and Charmin released NFT collectibles in 2021. Adidas recently launched a new metaverse project with Bored Ape Yacht Club. We’re likely to see more interesting brand marketing initiatives using NFTs. NFTs and the metaverse will become the new Instagram for brands. And just like on Instagram, many brands may start as NFT native. We’ll also see many more celebrities jumping in the bandwagon and using NFTs to enhance their personal brand.
9. Web2 companies will wake up and will try to get into Web3 — We’re already seeing this with Facebook trying to recast itself as a Web3 company. We’re likely to see other big Web2 companies dipping their toes into Web3 and metaverse in 2022. However, many of them are likely to create centralized and closed network versions of the metaverse.
10. Time for DAO 2.0 — We’ll see DAOs become more mature and mainstream. More people will join DAOs, prompting a change in definition of employment — never receiving a formal offer letter, accepting tokens instead of or along with fixed salaries, and working in multiple DAO projects at the same time. DAOs will also confront new challenges in terms of figuring out how to do M&A, run payroll and benefits, and coordinate activities in larger and larger organizations. We’ll see a plethora of tools emerge to help DAOs execute with efficiency. Many DAOs will also figure out how to interact with traditional Web2 companies. We’re likely to see regulators taking more interest in DAOs and make an attempt to educate themselves on how DAOs work.
Thanks to our customers and the ecosystem for an incredible 2021. Looking forward to another year of building the foundations for Web3. Wagmi.
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Christian Soschner
3 years ago
Steve Jobs' Secrets Revealed
From 1984 until 2011, he ran Apple using the same template.
What is a founder CEO's most crucial skill?
Presentation, communication, and sales
As a Business Angel Investor, I saw many pitch presentations and met with investors one-on-one to promote my companies.
There is always the conception of “Investors have to invest,” so there is no need to care about the presentation.
It's false. Nobody must invest. Many investors believe that entrepreneurs must convince them to invest in their business.
Sometimes — like in 2018–2022 — too much money enters the market, and everyone makes good money.
Do you recall the Buy Now, Pay Later Movement? This amazing narrative had no return potential. Only buyers who couldn't acquire financing elsewhere shopped at these companies.
Klarna's failing business concept led to high valuations.
Investors become more cautious when the economy falters. 2022 sees rising inflation, interest rates, wars, and civil instability. It's like the apocalypse's four horsemen have arrived.
Storytelling is important in rough economies.
When investors draw back, how can entrepreneurs stand out?
In Q2/2022, every study I've read said:
Investors cease investing
Deals are down in almost all IT industries from previous quarters.
What do founders need to do?
Differentiate yourself.
Storytelling talents help.
The Steve Jobs Way
Every time I watch a Steve Jobs presentation, I'm enthralled.
I'm a techie. Everything technical interests me. But, I skim most presentations.
What's Steve Jobs's secret?
Steve Jobs created Apple in 1976 and made it a profitable software and hardware firm in the 1980s. Macintosh goods couldn't beat IBM's. This mistake sacked him in 1985.
Before rejoining Apple in 1997, Steve Jobs founded Next Inc. and Pixar.
From then on, Apple became America's most valuable firm.
Steve Jobs understood people's needs. He said:
“People don’t know what they want until you show it to them. That’s why I never rely on market research. Our task is to read things that are not yet on the page.”
In his opinion, people talk about problems. A lot. Entrepreneurs must learn what the population's pressing problems are and create a solution.
Steve Jobs showed people what they needed before they realized it.
I'll explain:
Present a Big Vision
Steve Jobs starts every presentation by describing his long-term goals for Apple.
1984's Macintosh presentation set up David vs. Goliath. In a George Orwell-style dystopia, IBM computers were bad. It was 1984.
Apple will save the world, like Jedis.
Why do customers and investors like Big Vision?
People want a wider perspective, I think. Humans love improving the planet.
Apple users often cite emotional reasons for buying the brand.
Revolutionizing several industries with breakthrough inventions
Establish Authority
Everyone knows Apple in 2022. It's hard to find folks who confuse Apple with an apple around the world.
Apple wasn't as famous as it is today until Steve Jobs left in 2011.
Most entrepreneurs lack experience. They may market their company or items to folks who haven't heard of it.
Steve Jobs presented the company's historical accomplishments to overcome opposition.
In his presentation of the first iPhone, he talked about the Apple Macintosh, which altered the computing sector, and the iPod, which changed the music industry.
People who have never heard of Apple feel like they're seeing a winner. It raises expectations that the new product will be game-changing and must-have.
The Big Reveal
A pitch or product presentation always has something new.
Steve Jobs doesn't only demonstrate the product. I don't think he'd skip the major point of a company presentation.
He consistently discusses present market solutions, their faults, and a better consumer solution.
No solution exists yet.
It's a multi-faceted play:
It's comparing the new product to something familiar. This makes novelty and the product more relatable.
Describe a desirable solution.
He's funny. He demonstrated an iPod with an 80s phone dial in his iPhone presentation.
Then he reveals the new product. Macintosh presented itself.
Show the benefits
He outlines what Apple is doing differently after demonstrating the product.
How do you distinguish from others? The Big Breakthrough Presentation.
A few hundred slides might list all benefits.
Everyone would fall asleep. Have you ever had similar presentations?
When the brain is overloaded with knowledge, the limbic system changes to other duties, like lunch planning.
What should a speaker do? There's a classic proverb:
“Tell me and I forget, teach me and I may remember, involve me and I learn” (— Not Benjamin Franklin).
Steve Jobs showcased the product live.
Again, using ordinary scenarios to highlight the product's benefits makes it relatable.
The 2010 iPad Presentation uses this technique.
Invite the Team and Let Them Run the Presentation
CEOs spend most time outside the organization. Many companies elect to have only one presenter.
It sends the incorrect message to investors. Product presentations should always include the whole team.
Let me explain why.
Companies needing investment money frequently have shaky business strategies or no product-market fit or robust corporate structure.
Investors solely bet on a team's ability to implement ideas and make a profit.
Early team involvement helps investors understand the company's drivers. Travel costs are worthwhile.
But why for product presentations?
Presenters of varied ages, genders, social backgrounds, and skillsets are relatable. CEOs want relatable products.
Some customers may not believe a white man's message. A black woman's message may be more accepted.
Make the story relatable when you have the best product that solves people's concerns.
Best example: 1984 Macintosh presentation with development team panel.
What is the largest error people make when companies fail?
Saving money on the corporate and product presentation.
Invite your team to five partner meetings when five investors are shortlisted.
Rehearse the presentation till it's natural. Let the team speak.
Successful presentations require structure, rehearsal, and a team. Steve Jobs nailed it.
Eve Arnold
3 years ago
Your Ideal Position As a Part-Time Creator
Inspired by someone I never met
Inspiration is good and bad.
Paul Jarvis inspires me. He's a web person and writer who created his own category by being himself.
Paul said no thank you when everyone else was developing, building, and assuming greater responsibilities. This isn't success. He rewrote the rules. Working for himself, expanding at his own speed, and doing what he loves were his definitions of success.
Play with a problem that you have
The biggest problem can be not recognizing a problem.
Acceptance without question is deception. When you don't push limits, you forget how. You start thinking everything must be as it is.
For example: working. Paul worked a 9-5 agency work with little autonomy. He questioned whether the 9-5 was a way to live, not the way.
Another option existed. So he chipped away at how to live in this new environment.
Don't simply jump
Internet writers tell people considering quitting 9-5 to just quit. To throw in the towel. To do what you like.
The advice is harmful, despite the good intentions. People think quitting is hard. Like courage is the issue. Like handing your boss a resignation letter.
Nope. The tough part comes after. It’s easy to jump. Landing is difficult.
The landing
Paul didn't quit. Intelligent individuals don't. Smart folks focus on landing. They imagine life after 9-5.
Paul had been a web developer for a long time, had solid clients, and was respected. Hence if he pushed the limits and discovered another route, he had the potential to execute.
Working on the side
Society loves polarization. It’s left or right. Either way. Or chaos. It's 9-5 or entrepreneurship.
But like Paul, you can stretch polarization's limits. In-between exists.
You can work a 9-5 and side jobs (as I do). A mix of your favorites. The 9-5's stability and creativity. Fire and routine.
Remember you can't have everything but anything. You can create and work part-time.
My hybrid lifestyle
Not selling books doesn't destroy my world. My globe keeps spinning if my new business fails or if people don't like my Tweets. Unhappy algorithm? Cool. I'm not bothered (okay maybe a little).
The mix gives me the best of both worlds. To create, hone my skill, and grasp big-business basics. I like routine, but I also appreciate spending 4 hours on Saturdays writing.
Some days I adore leaving work at 5 pm and disconnecting. Other days, I adore having a place to write if inspiration strikes during a run or a discussion.
I’m a part-time creator
I’m a part-time creator. No, I'm not trying to quit. I don't work 5 pm - 2 am on the side. No, I'm not at $10,000 MRR.
I work part-time but enjoy my 9-5. My 9-5 has goodies. My side job as well.
It combines both to meet my lifestyle. I'm satisfied.
Join the Part-time Creators Club for free here. I’ll send you tips to enhance your creative game.
Zuzanna Sieja
3 years ago
In 2022, each data scientist needs to read these 11 books.
Non-technical talents can benefit data scientists in addition to statistics and programming.
As our article 5 Most In-Demand Skills for Data Scientists shows, being business-minded is useful. How can you get such a diverse skill set? We've compiled a list of helpful resources.
Data science, data analysis, programming, and business are covered. Even a few of these books will make you a better data scientist.
Ready? Let’s dive in.
Best books for data scientists
1. The Black Swan
Author: Nassim Taleb
First, a less obvious title. Nassim Nicholas Taleb's seminal series examines uncertainty, probability, risk, and decision-making.
Three characteristics define a black swan event:
It is erratic.
It has a significant impact.
Many times, people try to come up with an explanation that makes it seem more predictable than it actually was.
People formerly believed all swans were white because they'd never seen otherwise. A black swan in Australia shattered their belief.
Taleb uses this incident to illustrate how human thinking mistakes affect decision-making. The book teaches readers to be aware of unpredictability in the ever-changing IT business.
Try multiple tactics and models because you may find the answer.
2. High Output Management
Author: Andrew Grove
Intel's former chairman and CEO provides his insights on developing a global firm in this business book. We think Grove would choose “management” to describe the talent needed to start and run a business.
That's a skill for CEOs, techies, and data scientists. Grove writes on developing productive teams, motivation, real-life business scenarios, and revolutionizing work.
Five lessons:
Every action is a procedure.
Meetings are a medium of work
Manage short-term goals in accordance with long-term strategies.
Mission-oriented teams accelerate while functional teams increase leverage.
Utilize performance evaluations to enhance output.
So — if the above captures your imagination, it’s well worth getting stuck in.
3. The Hard Thing About Hard Things: Building a Business When There Are No Easy Answers
Author: Ben Horowitz
Few realize how difficult it is to run a business, even though many see it as a tremendous opportunity.
Business schools don't teach managers how to handle the toughest difficulties; they're usually on their own. So Ben Horowitz wrote this book.
It gives tips on creating and maintaining a new firm and analyzes the hurdles CEOs face.
Find suggestions on:
create software
Run a business.
Promote a product
Obtain resources
Smart investment
oversee daily operations
This book will help you cope with tough times.
4. Obviously Awesome: How to Nail Product Positioning
Author: April Dunford
Your job as a data scientist is a product. You should be able to sell what you do to clients. Even if your product is great, you must convince them.
How to? April Dunford's advice: Her book explains how to connect with customers by making your offering seem like a secret sauce.
You'll learn:
Select the ideal market for your products.
Connect an audience to the value of your goods right away.
Take use of three positioning philosophies.
Utilize market trends to aid purchasers
5. The Mom test
Author: Rob Fitzpatrick
The Mom Test improves communication. Client conversations are rarely predictable. The book emphasizes one of the most important communication rules: enquire about specific prior behaviors.
Both ways work. If a client has suggestions or demands, listen carefully and ensure everyone understands. The book is packed with client-speaking tips.
6. Introduction to Machine Learning with Python: A Guide for Data Scientists
Authors: Andreas C. Müller, Sarah Guido
Now, technical documents.
This book is for Python-savvy data scientists who wish to learn machine learning. Authors explain how to use algorithms instead of math theory.
Their technique is ideal for developers who wish to study machine learning basics and use cases. Sci-kit-learn, NumPy, SciPy, pandas, and Jupyter Notebook are covered beyond Python.
If you know machine learning or artificial neural networks, skip this.
7. Python Data Science Handbook: Essential Tools for Working with Data
Author: Jake VanderPlas
Data work isn't easy. Data manipulation, transformation, cleansing, and visualization must be exact.
Python is a popular tool. The Python Data Science Handbook explains everything. The book describes how to utilize Pandas, Numpy, Matplotlib, Scikit-Learn, and Jupyter for beginners.
The only thing missing is a way to apply your learnings.
8. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
Author: Wes McKinney
The author leads you through manipulating, processing, cleaning, and analyzing Python datasets using NumPy, Pandas, and IPython.
The book's realistic case studies make it a great resource for Python or scientific computing beginners. Once accomplished, you'll uncover online analytics, finance, social science, and economics solutions.
9. Data Science from Scratch
Author: Joel Grus
Here's a title for data scientists with Python, stats, maths, and algebra skills (alongside a grasp of algorithms and machine learning). You'll learn data science's essential libraries, frameworks, modules, and toolkits.
The author works through all the key principles, providing you with the practical abilities to develop simple code. The book is appropriate for intermediate programmers interested in data science and machine learning.
Not that prior knowledge is required. The writing style matches all experience levels, but understanding will help you absorb more.
10. Machine Learning Yearning
Author: Andrew Ng
Andrew Ng is a machine learning expert. Co-founded and teaches at Stanford. This free book shows you how to structure an ML project, including recognizing mistakes and building in complex contexts.
The book delivers knowledge and teaches how to apply it, so you'll know how to:
Determine the optimal course of action for your ML project.
Create software that is more effective than people.
Recognize when to use end-to-end, transfer, and multi-task learning, and how to do so.
Identifying machine learning system flaws
Ng writes easy-to-read books. No rigorous math theory; just a terrific approach to understanding how to make technical machine learning decisions.
11. Deep Learning with PyTorch Step-by-Step
Author: Daniel Voigt Godoy
The last title is also the most recent. The book was revised on 23 January 2022 to discuss Deep Learning and PyTorch, a Python coding tool.
It comprises four parts:
Fundamentals (gradient descent, training linear and logistic regressions in PyTorch)
Machine Learning (deeper models and activation functions, convolutions, transfer learning, initialization schemes)
Sequences (RNN, GRU, LSTM, seq2seq models, attention, self-attention, transformers)
Automatic Language Recognition (tokenization, embeddings, contextual word embeddings, ELMo, BERT, GPT-2)
We admire the book's readability. The author avoids difficult mathematical concepts, making the material feel like a conversation.
Is every data scientist a humanist?
Even as a technological professional, you can't escape human interaction, especially with clients.
We hope these books will help you develop interpersonal skills.